Machine Learning Engineer

Saris AI, based in San Francisco with teams in Montreal and Toronto, develops advanced agentic AI systems for the banking industry. The company focuses on automating complex workflows that require long-context reasoning, integration with legacy systems, and strict compliance. With live AI agents already supporting real customer operations, Saris AI is expanding quickly and seeking technical leaders who want to shape the future of work in banking. Role overview This is a hands-on leadership position within the core engineering team in San Francisco. The Machine Learning Engineering Lead will guide machine learning systems from initial concept through scaling, helping define both the technical vision and the supporting infrastructure. What you will do Oversee the ML/AI function end to end, setting technical direction and standards across the company. Design and supervise development of multi-modal, agentic AI systems that power live customer workflows. Build and manage evaluation frameworks, datasets, and metrics to improve agent performance. Drive productionization of ML systems with an emphasis on reliability, scalability, and compliance. Recruit, develop, and mentor a high-performing ML team, fostering strong practices in modeling, experimentation, and deployment. Requirements 8+ years of experience in machine learning or AI engineering, including time as a technical lead or manager. Proven track record leading ML projects from concept to production deployment. Expertise with large language models (LLMs) and/or agentic systems, especially in customer-facing products. Strong grasp of ML fundamentals: deep learning, transformers, model evaluation, and trade-offs. Hands-on experience scaling ML systems in production, with a focus on monitoring, iteration, and reliability. Ability to lead engineering teams, influence architecture, and set technical direction. Comfort working in early-stage, ambiguous, and rapidly changing environments.

Join Our Team as a Machine Learning EngineerSaris-AI is a pioneering applied AI startup, based in San Francisco and Montreal, focused on revolutionizing the banking sector. Our mission is to address a colossal $100 billion/year challenge that is rapidly expanding, innovating the limits of what can be achieved with advanced multi-turn AI systems.We aim to automate complex workflows that necessitate long-context reasoning, orchestration of tools across legacy systems, and rigorous compliance processes—solving problems that currently lack definitive solutions.Our team has successfully deployed AI agents that manage real customer workflows effectively in production. As we expand our customer base and accelerate our growth, we are in search of highly skilled technical builders who aspire to make a significant impact in the early stages of our journey.As a foundational Machine Learning Engineer, you will own our entire ML stack and bring custom agents to life.

About UsAt Citizen Health, we believe that the right advocate can significantly enhance healthcare experiences and outcomes. Founded on the principles of personal healthcare journeys, we leverage a unique combination of data, artificial intelligence, and community engagement to craft a personalized AI advocate. Our platform harnesses patients' comprehensive medical histories alongside data from a vast network of individuals, providing tailored insights for effective clinical decisions and everyday challenges. We focus initially on rare and complex conditions, allowing patients to share their information for mutual benefit, while empowering biopharma and researchers with regulatory-grade data that accelerates the drug development process for critical treatments.Our team consists of seasoned entrepreneurs with successful track records, backed by esteemed investors such as 8VC, Transformation Capital, and Headline Ventures. We are passionate about reshaping the future of consumer healthcare.Position OverviewCitizen Health is on the lookout for talented AI/Machine Learning Engineers to spearhead the development and implementation of innovative AI solutions for our patient-centered platform. This pivotal role involves crafting and deploying advanced machine learning models that convert intricate health data into actionable insights for patients, healthcare professionals, and researchers.As a vital technical leader, you will be at the cutting edge of applying sophisticated machine learning methodologies to tackle complex challenges in rare disease research and patient care. Your contributions will be crucial in developing AI-driven solutions that enhance disease comprehension, treatment options, and overall patient outcomes.Key ResponsibilitiesDesign and execute comprehensive machine learning solutions, covering data preprocessing to model deployment and ongoing monitoring.Develop and refine advanced Large Language Models (LLMs) tailored for healthcare applications, utilizing techniques such as fine-tuning and Retrieval-Augmented Generation (RAG).Construct robust data pipelines for validation and deployment processes.Implement machine learning systems capable of processing and analyzing diverse healthcare data types, including structured clinical data, medical imaging, and unstructured text.Collaborate closely with backend engineers to seamlessly integrate ML models into our production infrastructure.Ensure that ML systems adhere to rigorous healthcare compliance standards while maintaining optimal performance.

Superhuman embraces a hybrid working model designed to offer team members the ideal balance of focused work and collaborative, in-person interactions that cultivate trust, innovation, and a vibrant team culture.About SuperhumanSuperhuman, now inclusive of Grammarly, is an AI productivity platform dedicated to unleashing the superhuman potential within everyone. Our suite of applications and agents extends AI capabilities across 1 million+ applications and websites. Our products include Grammarly's writing assistance, Coda's collaborative workspaces, Mail's inbox management, and Go, a proactive AI assistant that intuitively understands context and provides automated support. Since our inception in 2009, Superhuman has empowered over 40 million individuals, 50,000 organizations, and 3,000 educational institutions globally to reduce busywork and concentrate on what truly matters. Discover more at superhuman.com and explore our core values here.The OpportunitiesJoin us in developing a groundbreaking platform for AI Agents, designed to collaboratively tackle complex tasks, utilizing Superhuman's intuitive UI. As a Machine Learning Engineer on this pioneering team, you will play a critical role in our company's transformation.Shape the Future of Productivity: Take on a vital role in evolving Grammarly from a cherished writing assistant into an indispensable AI-driven productivity suite for enterprises.Build an Innovative AI Agent Platform: Lead the charge in creating a new platform where multiple AI agents work together to address intricate user challenges. You will oversee the core orchestration, routing, and planning systems.Own Key ML Systems: Design and implement advanced machine learning models that enhance core product experiences, including search ranking and proactive suggestions that anticipate user needs.

Saris AI develops applied AI solutions for the banking sector, with teams in San Francisco, Montreal, and Toronto. The company builds automation tools that handle complex, long-context reasoning and agent-driven decision-making. Reliability and compliance shape every product, and Saris AI's agents already manage real customer workflows in production. As revenue grows, the engineering team is expanding to enhance current offerings and explore new directions. The Senior Machine Learning Engineer role is based in San Francisco and sits within the core engineering group. The team works in a collaborative, early-stage setting, balancing infrastructure needs with the delivery of features that serve customers directly. What you will do Build and maintain machine learning infrastructure, such as evaluation frameworks, prompt management systems, and tools for model observability. Develop new AI features for customers while supporting and improving the underlying infrastructure. Shape strategies for evaluation, LLM routing, prompt engineering, and model selection. Set practical standards to boost quality without slowing down development. Guide technical direction by clarifying trade-offs and architectural choices. Requirements Minimum 4 years of experience in machine learning or AI engineering, including production deployment of ML systems. Direct experience with large language models, prompt engineering, evaluation techniques, and model routing. Background in building tools and systems that deliver value to users. Comfort making pragmatic trade-offs and recognizing when a solution is sufficient. Ability to navigate ambiguity, define problems, and deliver results independently. Strong focus on end users and understanding the impact of ML decisions on customer experience. Supports team growth through code reviews, collaboration, and clear technical communication. Bonus Experience in regulated industries, especially banking.

Founding Machine Learning EngineerLocation: San Francisco, CA Work Model: In-office 5 days a weekAbout UsAt Effective AI, we are pioneering the future of work. Our vision is to push the boundaries of AI beyond mere repetitive tasks, focusing instead on intricate knowledge work that requires expertise and multi-faceted reasoning. We are developing advanced AI Teammates that are designed to navigate complex workflows and collaborate seamlessly with human professionals. Our initial focus is on the trillion-dollar U.S. Property & Casualty insurance sector, a domain rich with complexity and data, making it an ideal arena for our innovations.We proudly secured $10 million in seed funding from prominent investors including Lightspeed Ventures and Valor Equity Partners.Our committed team is based in San Francisco and thrives on in-person collaboration to tackle these significant challenges.Your RoleAs a Founding Machine Learning Engineer, you will be an integral member of our founding team, responsible for architecting, training, and deploying the agent loops that power our AI Teammates from inception. You will address some of the most pressing challenges in agentic AI and natural language processing, developing AI solutions adept at performing essential insurance functions such as underwriting and claims processing.Your responsibilities will include:Architecting and Developing Core ML Pipelines: Design, train, and fine-tune cutting-edge language models (including reinforcement learning agents) to facilitate long-term task accomplishment and complex decision-making.Implementing Nuanced Reasoning: Integrate machine learning techniques that empower agents to make informed decisions based on ambiguous or incomplete data, akin to human expert reasoning and generalization.Building Intelligent, Tool-Using Agents: Engineer the ML systems that enable our agents to dynamically select and utilize a broad array of external tools—including APIs, databases, web searches, and Excel-based pricing algorithms—to gather necessary information and execute actions.Designing and Implementing Robust Evaluation Frameworks: Create and employ comprehensive evaluation metrics and systems to rigorously assess and benchmark agent performance, identify areas for enhancement, and guarantee reliability and safety in real-world insurance processes.Enabling Continuous Adaptation and Learning: Develop resilient ML pipelines and feedback loops that facilitate ongoing learning and adaptation.

About Liquid AIFounded as a spin-off from MIT CSAIL, Liquid AI specializes in creating versatile AI systems designed for optimal performance across various deployment platforms, including data center accelerators and on-device hardware. Our technology emphasizes low latency, minimal memory consumption, privacy, and dependability. We collaborate with leading enterprises in sectors such as consumer electronics, automotive, life sciences, and financial services. As we experience rapid growth, we are on the lookout for exceptional talent to join our team.The OpportunityThe Data team at Liquid AI drives the development of our Liquid Foundation Models, focusing on pre-training, vision, audio, and emerging modalities. With the stagnation of public data sources, the effectiveness of our models increasingly relies on specially curated datasets. We are seeking engineers with a machine learning mindset who can efficiently gather, filter, and synthesize high-quality data at scale.At Liquid AI, we regard data as a research challenge rather than an infrastructural issue. Our engineers conduct experiments, design ablations, and assess how data-related decisions impact model quality. We will align you with a team where you can experience rapid growth and make a significant impact, be it in pre-training, post-training reinforcement learning, vision-language, audio, or multimodal applications.While we prefer candidates in San Francisco and Boston, we are open to considering other locations.What We're Looking ForWe are in search of a candidate who:Thinks like a researcher and executes like an engineer: You should be able to formulate hypotheses, conduct experiments, and evaluate results. Our engineers produce research-level code while our researchers implement production systems.Learns quickly and adapts: You will be working in rapidly evolving modalities, so the ability to quickly grasp new domains and thrive in ambiguity is essential.Prioritizes data quality: We hold data quality in high regard; tasks such as filtering, deduplication, augmentation, and evaluation are key responsibilities, not afterthoughts.Solves problems autonomously: Data engineers operate within training groups (pre-training and multimodal). While collaboration is crucial, we expect ownership and self-direction.The WorkDevelop and maintain data processing, filtering, and selection pipelines at scale.Establish pipelines for pretraining, midtraining, supervised fine-tuning, and preference optimization datasets.Design synthetic data generation systems utilizing large language models (LLMs), structured prompting, and domain-specific generative techniques.

At Superhuman, we embrace a dynamic hybrid working model, allowing team members to enjoy a balance of focused work time and collaborative in-person interactions that foster trust, innovation, and a vibrant team culture.About SuperhumanSuperhuman, now inclusive of Grammarly, is an innovative AI productivity platform dedicated to unlocking the superhuman potential in individuals. Our suite of applications and agents seamlessly integrates AI into the workflow, connecting with over a million applications and websites. Our products range from Grammarly’s writing assistance to Coda’s collaborative environments, Mail’s inbox management, and Go, a proactive AI assistant that understands context and provides assistance automatically. Since our inception in 2009, Superhuman has empowered over 40 million users across 50,000 organizations and 3,000 educational institutions globally, enabling them to eliminate busywork and concentrate on what truly matters. Discover more atsuperhuman.com and explore our values here.The OpportunitiesJoin our team as we develop a pioneering platform for AI Agents to collaboratively tackle complex tasks using Superhuman's intuitive UI. As a Machine Learning Engineer, you will be a key player in our company's transformation.Shape the Future of Productivity: Be instrumental in transitioning Grammarly from a beloved writing companion to a crucial, AI-driven productivity suite for enterprises.Build a Groundbreaking AI Agent Platform: Lead the creation of a new platform where AI agents work together to address intricate user challenges. You will manage the essential orchestration, routing, and planning systems.Own Critical ML Systems: Design and implement advanced ML models for fundamental product experiences, including search ranking and proactive suggestions that foresee user needs.Integrate Cutting-Edge AI: Work at the cutting edge of AI technology, developing ML components that utilize the latest models to craft extraordinary user experiences.Thrive in a High-Impact Environment: Join a foundational team where you will enjoy a high level of autonomy and product insight in a fast-paced, evolving atmosphere.

Join our dynamic Personalization team at Boomtrain as a Machine Learning Engineer. We are in search of a skilled engineer who will play a pivotal role in developing and enhancing our recommendation systems that cater to a variety of customers.In this role, you will collaborate with a talented team dedicated to designing and implementing innovative models and systems that deliver personalized recommendations. You will have the opportunity to work on complex engineering challenges and contribute to generating hundreds of millions of recommendations daily.This position offers a unique chance to engage in end-to-end project work and make a significant impact on our personalization initiatives.Key Responsibilities:Research and propose advanced recommendation and optimization models to enhance our personalization systems.Develop and maintain offline model generation pipelines.Design and maintain online recommendation serving systems.

Join Retell AI as a Senior Machine Learning EngineerRetell AI is at the forefront of revolutionizing the call center industry using groundbreaking voice AI technology. Within just 18 months of our inception, we have empowered thousands of businesses with our AI voice agents capable of managing sales, support, and logistics calls that traditionally required extensive human teams.Supported by renowned investors, including Y Combinator and Alt Capital, our journey has seen us scale from $5M to an impressive $36M ARR with a dedicated team of 20. Our ambition for 2026 is to develop a state-of-the-art customer experience platform, transforming entire contact centers with AI. We are building intelligent AI “workers” that will serve as frontline agents, quality assurance analysts, and managers—constantly executing, monitoring, and enhancing customer interactions.We are rapidly expanding and seeking passionate innovators eager to solve complex technical challenges and make a tangible impact in one of the fastest-growing voice AI startups. Together, let's shape the future of customer interactions.

Join Our Innovative Team at HiveHive is at the forefront of cloud-based AI solutions, revolutionizing how organizations understand, search for, and generate content. Trusted by many of the world's largest and most groundbreaking companies, we empower developers with premier pre-trained AI models that handle billions of API requests monthly. Our turnkey software applications leverage proprietary AI models and datasets, driving transformative advancements in content moderation, brand protection, sponsorship measurement, and context-based ad targeting.With over $120M in funding from prominent investors like General Catalyst, 8VC, Glynn Capital, Bain & Company, and Visa Ventures, Hive is rapidly expanding. Our dynamic team of over 250 employees operates from our San Francisco, Seattle, and Delhi offices. If you are passionate about shaping the future of AI, we invite you to explore opportunities with us!About the Machine Learning Engineer RoleAs we strive to achieve our ambitious vision, we seek exceptional machine learning engineers to join our team. We are looking for enthusiastic developers who are eager to remain at the cutting edge of deep learning technology, designing and deploying state-of-the-art neural network models into production. Our ideal candidates thrive in working with large-scale datasets and demonstrate a keen interest in mastering new technologies across the machine learning spectrum. We value individuals who are proactive and take ownership of their projects, contributing innovative ideas and practical implementations. Experience in building machine learning applications from the ground up and designing scalable, maintainable data pipelines is essential.

About UsAt XOXO AI, we are at the forefront of innovation, crafting intelligent interfaces that seamlessly integrate into everyday life. As a dynamic research lab comprised of dedicated engineers, designers, and researchers, we tackle unique challenges that extend beyond the workplace.Having achieved significant breakthroughs in infrastructure, architecture, and model layers, we are looking for passionate builders to help us realize our vision through the development of robust interface and application layers.About the RoleWe seek a talented Data/Machine Learning Engineer to establish our data infrastructure and production-ready ML systems, ensuring our product is responsive, dependable, and intelligent. This full-cycle role involves designing high-throughput pipelines, defining resilient data models, and deploying low-latency feature and model serving that can withstand real-world demands.You will collaborate closely with our founders and the early engineering team to transition prototypes into production, transforming complex real-world signals into reliable datasets and real-time functionalities that enhance core product experiences.What You’ll DoDevelop and manage high-throughput batch and streaming pipelines for analytics, training, and product signals.Lead real-time feature pipelines and online feature serving for low-latency inference.Design and oversee dimensional data models, skillfully managing schema evolution to avoid disrupting downstream consumers.Optimize model serving infrastructure to meet stringent latency and reliability service level objectives (SLOs).Establish and enforce event schemas, telemetry standards, and data contracts across multiple teams.Collaborate with engineering, product, and research teams to translate ambiguous product requirements into measurable, sustainable systems.

Charter:Join us as a pivotal member of a groundbreaking team dedicated to revolutionizing the field of toxicology by developing advanced AI systems that will replace traditional lab and animal experiments.What We Seek:We are on the lookout for exceptional individuals who can inspire those around them and drive the team towards greatness. Our ideal candidate is someone with high agency—able to identify priorities and take action. We value unique passions and hobbies that may seem niche but reveal a deep commitment and curiosity when explored. Candidates should approach challenges with both intentionality and a sense of wonder, embodying the spirit of exploration akin to an immigrant in a new land or a self-taught coder. A strong desire to learn and grow, coupled with technical excellence and a commitment to mastering one’s craft, is essential. We want those who are willing to tackle daunting challenges and derive satisfaction from the journey as much as the outcome.Your Responsibilities:Establish the foundational end-to-end ML/AI system, including wetlab data generation, data cleaning/processing, model architecture, training, inference, and deployment strategies.Lead innovative research and development initiatives focused on elucidating the interplay between chemistry and biology.Design and scale large models that are pretrained on paired chemistry and biological imagery.Conduct applied research aimed at optimizing, aggregating, and pooling embeddings.Become a thought leader in emerging and underexplored domains, such as molecular graph representations and generative diffusion for biological applications.Develop entrepreneurial skills alongside engineering expertise by creating impactful solutions that deliver substantial value for scientists.Deliver outstanding technology and products that redefine industry standards.Preferred Attributes:...

About Hike Medical Hike Medical is building the future of musculoskeletal care by combining advanced technology with practical healthcare solutions. Based in San Francisco’s Rincon Hill, the team develops a platform that spans three core areas: an AI-powered vision system for rapid web-based foot scans that generate custom 3D-printed orthotics, an AI agent platform that manages the entire DME workflow from intake through claims, and SoleForge, a high-scale 3D printing facility for custom medical devices. Hike Medical partners with some of the world’s largest employers and major orthotics and prosthetics organizations. Fortune 50 companies trust the platform to support employee well-being, and a broad network of clinical partners keeps the company connected to real-world needs. Custom insoles are just the starting point. The long-term goal is to reshape the industry with bionic devices: AI-designed, robotically manufactured orthotic and prosthetic products. The company aims to reach this milestone by 2040. Learn more at bionics2040.com. With $22 million raised across Seed and Series A rounds from leading investors, Hike Medical offers a results-oriented culture for those interested in the intersection of AI, manufacturing, and healthcare.

Company Overview At Specter, we are pioneering a software-defined "control plane" designed to enhance the real-world perception of physical assets. Our mission begins with safeguarding American businesses by providing them with comprehensive insights into their physical environments.To achieve this, we are developing a robust hardware-software ecosystem leveraging multi-modal wireless mesh sensing technology. This innovation allows us to significantly reduce the cost and time involved in sensor deployment by a factor of ten. Ultimately, our platform aims to serve as the perception engine for businesses, facilitating real-time visibility and autonomous management of their operational perimeters.Our co-founders, Xerxes and Philip, are deeply committed to empowering our partners in the rapidly evolving landscape of physical AI and robotics. We are a dynamic, rapidly expanding team comprised of talent from Anduril, Tesla, Uber, and the U.S. Special Forces.Position Overview Specter is seeking a dedicated Machine Learning Infrastructure Engineer to construct and optimize the ML systems that drive real-time perception and inference capabilities across our edge-cloud platform. This position will involve overseeing the training, deployment, and enhancement of computer vision and sensor fusion models, aimed at enabling autonomous monitoring and decision-making for our clients' physical assets.Key Responsibilities Include:Design and implement scalable ML training pipelines for computer vision applications, including object detection, tracking, classification, and segmentation.Develop efficient model serving infrastructures to facilitate real-time inference on edge devices with limited computational and power resources.Optimize models for deployment on embedded hardware, employing techniques such as quantization, pruning, TensorRT, ONNX, and CoreML.Create continuous training and evaluation systems to enhance model performance through feedback loops derived from production data.Establish data pipelines for the ingestion, labeling, versioning, and management of extensive multi-modal sensor datasets, including video, radar, lidar, and thermal data.Implement model monitoring frameworks, A/B testing methodologies, and performance analytics for deployed perception systems.Collaborate with perception researchers to transition models from research environments to scalable production across thousands of edge nodes.Construct tools and infrastructure for distributed training, hyperparameter optimization, and experiment tracking.

Join Hive as a Senior Machine Learning Engineer and help shape the future of AI! We are seeking passionate individuals who excel at developing and deploying cutting-edge deep learning models. In this role, you will work with large-scale datasets to create innovative machine learning solutions, collaborating closely with a talented team of engineers to push the boundaries of artificial intelligence. Ideal candidates will have a proven track record of building and scaling machine learning projects from conception to production, along with a strong commitment to continuous learning and personal ownership in their work.

Be Part of the Future of Autonomous RoboticsAt Bedrock Robotics, we are pioneering the transition of AI from theoretical frameworks to practical applications in the built environment. Our team is comprised of seasoned professionals who have been instrumental in the success of innovative companies such as Waymo, Segment, and Uber Freight. We are at the forefront of deploying autonomous technologies in heavy construction machinery, significantly enhancing the efficiency and safety of multi-billion dollar infrastructure projects across the nation.With backing from $350 million in funding, our mission is to address the urgent need for housing, data centers, and manufacturing facilities, while simultaneously responding to the construction industry's labor shortages.This position is where cutting-edge algorithms meet the practical world of construction. You will work alongside industry experts and top-tier engineers to tackle complex real-world challenges that cannot be simulated. If you are eager to leverage advanced technology for impactful problem-solving within a skilled team, we encourage you to apply.

Join Databricks Mosaic AI as a Senior Machine Learning Engineer and take the lead in developing our cutting-edge generative AI platform. Our team, formed in late 2020, empowers businesses by allowing them to securely fine-tune, train, and deploy custom AI models using their own data. This ensures maximum security and control while being compatible with all major cloud providers, allowing for unparalleled flexibility in AI development.Since our integration into Databricks in July 2023, we have been dedicated to tackling some of the world's most challenging problems, from revolutionizing transportation to accelerating medical advancements. We leverage deep data insights to enhance our customers' business capabilities and thrive on overcoming technical challenges to deliver superior data and AI solutions.Role Overview:As a Senior Machine Learning Engineer, you will play a pivotal role in the design and implementation of our generative AI platform, covering the entire ML development lifecycle, including data generation, training, evaluation, serving, and agent-building. Your expertise will be essential in translating user requirements into intuitive product interfaces while constructing robust backend distributed systems that drive these features.

At Genies, we are revolutionizing the way artificial intelligence interacts with users through our cutting-edge AI avatar technology. Our proprietary framework empowers AI to embody fully realized personas that think, behave, and interact like real individuals. With applications spanning various sectors including enterprise, consumer, entertainment, and gaming, we are proud to lead the charge in bringing AI companions and agents to life. Backed by notable investors such as Silver Lake, BOND, and Bob Iger, we believe that every online presence will have an AI persona.About the Role:We are on the lookout for a passionate and skilled Senior Machine Learning Engineer to become a vital part of our AI team in San Francisco, CA. In this pivotal role, you will own the research and development of our core AI avatar chat systems, shaping the technical roadmap that drives the intelligence, personality, and interactivity of millions of AI avatars.By addressing fundamental technical challenges, your efforts will help create engaging, autonomous, and inspiring AI companions. Collaborating with a dedicated team of engineers and researchers, you will connect cutting-edge AI research with practical, consumer-facing applications.Key Responsibilities:Explore and implement advanced solutions utilizing foundation models, prompt engineering, retrieval-augmented generation (RAG), knowledge graphs, and multi-agent architectures, along with traditional machine learning methods for a multi-modal AI chat product.Design, implement, and deploy scalable AI features and agentic systems within our backend architecture.Develop and execute comprehensive quantitative benchmarks to assess and enhance our AI features and systems.Collaborate with the product team to iterate and refine AI systems based on user feedback and performance metrics.Work in tandem with AI researchers to transform experimental outputs into stable, production-ready backend solutions.Establish, implement, and uphold best practices for AI agent quality assurance, safety, and cost management.Tune and train large language models and other machine learning models when off-the-shelf solutions fall short.Stay updated on the latest academic and industry research in large language models and AI agents, proactively identifying and testing innovative techniques to enhance our technology stack.