Senior Machine Learning Engineer

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.

The Bot CompanyAt The Bot Company, we are on a mission to create an innovative robotic assistant for every household.Our dynamic team, composed of talented engineers, designers, and operators, is based in San Francisco. We have a rich background from industry leaders such as Tesla, Cruise, OpenAI, Google, and Pixar, and we have successfully delivered products to hundreds of millions of users, honing our ability to create exceptional products and experiences.We pride ourselves on maintaining a streamlined team structure that fosters swift decision-making and minimizes bureaucracy. Each member is considered an Individual Contributor, granted substantial autonomy, ownership, and accountability. Our culture enables us to work across the technology stack with an emphasis on rapid iteration and execution.What We Seek in CandidatesCandidates for all positions at The Bot Company must exhibit remarkable sharpness and the capacity to thrive in high-pressure environments. We expect candidates to showcase:Exceptional Cognitive Abilities: You possess quick thinking, instant learning capabilities, and the ability to reason across diverse domains.Engineering Curiosity: You demonstrate an innate desire to understand how systems function, even beyond your area of expertise.Performance-Driven Attitude: You excel in fast-paced settings, effectively navigate ambiguity, and thrive under demanding circumstances.Machine Learning: Multimodal Foundation ModelsWe are developing unified foundation models capable of reasoning across text, images, video, and kinematics to inform intelligent robotic behaviors.You will engage with large-scale multimodal networks, overseeing the complete process from data handling to model training and deployment.Your ResponsibilitiesConstruct Native Multimodal Policies: Create architectures where vision, language, and other modalities are represented in a unified manner.Enhance Cross-Modal Reasoning: Explore and implement strategies to ensure that the model not only correlates modalities but also comprehends them (e.g., linking visual physics to kinematic constraints).Manage the Training Loop from Start to Finish: Design, execute, troubleshoot, and refine large-scale training experiments; identify failure points, enhance data mixtures, and tighten evaluations to achieve measurable improvements.Deploy and Refine Real Systems: Integrate models into practical robotic frameworks, enhance robot code for model deployment, and optimize performance for edge inference.

Bland Inc. seeks a Machine Learning Researcher specializing in Multimodal Large Language Models (LLMs) to join the team in San Francisco. The focus is on advancing AI systems that integrate language with other types of data. Role overview This position centers on research and development aimed at improving how AI models process and understand information from multiple sources, such as text combined with images or other modalities. What you will do Investigate how language interacts with additional data types within multimodal LLMs Create and evaluate new methods to enhance AI model performance Work closely with colleagues on projects designed to push the boundaries of machine learning Location This role is based in San Francisco.

Join VOLT, a trailblazer in crafting advanced AI perception systems that enhance safety and security through real-time risk detection in the physical world.We are on the lookout for a Senior Applied AI & Machine Learning Engineer dedicated to designing, optimizing, and deploying multimodal AI models capable of functioning reliably in diverse real-world scenarios. This is a hands-on role focused on transitioning models from conceptual data to practical production, encompassing both edge devices and cloud infrastructures.In this position, you will engage with vision, video, and language-based models that interpret real-world scenes and events, ensuring their accuracy, latency, robustness, and cost-effectiveness in production systems.Reporting directly to the Head of Engineering, you will play a pivotal role in advancing VOLT AI’s core perception platform.

Our MissionAt Altos Labs, we are dedicated to restoring cell health and resilience through innovative cell rejuvenation techniques aimed at reversing diseases, injuries, and disabilities that can arise throughout life.For further insights, please visit our website at altoslabs.com.Our ValueOur singular Altos Value is: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe firmly believe that diverse perspectives are crucial for scientific innovation. At Altos, exceptional scientists and industry leaders collaborate globally to further our shared mission. We prioritize Belonging, ensuring all employees feel valued for their unique perspectives, and we hold ourselves accountable for maintaining a diverse and inclusive environment.Your Contributions to AltosAs a member of our team, you will accelerate and enhance our efforts in developing unified, multi-modal generative foundation models tailored for multiscale biology. You will be a key player in multidisciplinary teams that create the computational platforms essential for Altos to fulfill its mission.In this position, you will collaborate with other scientists and engineers across the Institute of Computation to design, develop, and scale cutting-edge foundation models that address biological inquiries and assist in discovering novel interventions for aging and disease. Your focus will be on synthesizing unstructured multimodal signals with structured relational data and knowledge graphs that depict biological realities.The ideal candidate will excel in a dynamic environment that values teamwork, transparency, scientific excellence, originality, and integrity.

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.

Tavus – Multimodal AI Model OptimizationResearch EngineerAt Tavus, we are pioneering the human aspect of AI technology. Our objective is to make human-AI interactions as seamless and natural as in-person conversations, allowing for a human touch in areas that were once considered unscalable.We accomplish this through groundbreaking research in multimodal AI, focusing on human-to-human communication modeling (encompassing language, audio, and video) and the development of audio-visual avatar behaviors. Our innovative models drive applications ranging from text-to-video AI avatars to real-time conversational video experiences across sectors such as healthcare, recruitment, sales, and education.By empowering AI to perceive, listen, and engage with an authentic human-like presence, we are laying the groundwork for the next generation of AI workers, assistants, and companions.As a Series B company, we are supported by renowned investors, including Sequoia, Y Combinator, and Scale VC. Join us as we shape the future of human-AI interaction.The RoleWe are seeking an accomplished Research Scientist/Engineer with expertise in model optimization to be a vital part of our core AI team.The ideal candidate thrives in dynamic startup environments, is adept at setting priorities independently, and is open to making calculated decisions. We are moving swiftly and need individuals who can help navigate our path forward.Your MissionTransform state-of-the-art research models into fast, efficient, and production-ready systems through techniques such as sparsification, distillation, and quantization.Oversee the optimization lifecycle for critical models: establish metrics, conduct experiments, and evaluate trade-offs among latency, cost, and quality.Collaborate closely with researchers and engineers to convert innovative concepts into deployable solutions.RequirementsExtensive experience in deep learning with PyTorch.Practical experience in model optimization and compression, including knowledge distillation, pruning/sparsification, quantization, and mixed precision.Familiarity with efficient architectures such as low-rank adapters.Strong grasp of inference performance and GPU/accelerator fundamentals.Proficient in Python coding and adherence to best practices in research engineering.Experience with large models and datasets in cloud environments.Capability to read ML literature, reproduce results, and modify ideas accordingly.

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.

About VSCO At VSCO, we empower photographers with an innovative platform that provides essential tools, a vibrant community, and the visibility needed for creative and professional growth. We cultivate an authentic creative environment that welcomes photographers of all skill levels, offering a space that inspires opportunity, collaboration, and connection. Our mission is to support photographers in their journeys, enabling them to thrive and connect with fellow creatives and businesses through our comprehensive suite of tools, available on both mobile and desktop. We seek individuals who are passionate and proactive in advancing our mission. Our team members have the opportunity to make a significant impact, and we believe that collaborative efforts yield stronger results. Our core values are essential to our team culture and guide our hiring process. Learn more about what you can expect when joining VSCO on our Careers Page. About The Role As a Senior Machine Learning Engineer, you will harness the power of AI and machine learning to create innovative, reliable user-facing product features. You will leverage your extensive technical background and hands-on experience in deploying machine learning models to deliver impactful solutions based on real-world feedback. Your focus on measurable outcomes and customer satisfaction drives your work, blending innovation with practical implementation. You will be highly skilled in Python and adept across the data and machine learning stack, enabling you to develop and launch models efficiently while ensuring scalability and maintainability. Whether working with traditional algorithms or cutting-edge deep learning and generative AI, you will expertly navigate the complexity of each problem, managing every phase from defining the challenge to deployment and iterative improvement. Your dedication to software engineering excellence will inform your thoughtful approach to system design for machine learning, encompassing data quality, pipeline design, feature workflows, model serving, and ongoing monitoring and enhancement. By integrating machine learning deeply within our cohesive product experiences, you will collaborate effectively with cross-functional teams, aligning on objectives, defining success metrics, and driving meaningful outcomes. You will stay informed about the rapidly evolving AI landscape, maintaining a discerning perspective that allows your team to focus on significant advancements while avoiding distractions. The Day to Day Design and implement ML-powered features for search, discovery, personalization, and more.

Join Lightning AI as a Senior Application Security Engineer specializing in the realms of Artificial Intelligence and Machine Learning. In this pivotal role, you'll be responsible for enhancing our application security posture across our innovative platforms. Collaborate with a team of talented engineers to identify vulnerabilities, implement security best practices, and ensure our AI-driven solutions remain robust and secure.

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.

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.

P-1380 Join Databricks as a Senior Applied AI Engineer, where you will harness the power of machine learning, scheduling, and optimization algorithms to enhance the efficiency and performance of our engineering systems and infrastructure. Our Applied AI team tackles some of the most challenging and fascinating issues in the industry, ensuring that Databricks infrastructure and products operate at peak performance and cost efficiency. This role is critical, as our customers depend on us to deliver the most optimized workloads. Your Impact: Develop comprehensive systems from the ground up within a dynamic team of seasoned professionals. Influence the direction of our applied machine learning investment areas by collaborating with engineering and product teams across the organization. Lead the design and implementation of advanced AI models and systems that enhance the capabilities and performance of Databricks' products, infrastructure, and services. Architect and deploy robust, scalable machine learning infrastructure, including data storage, processing, model training, serving components, and monitoring systems to facilitate seamless integration of AI/ML models into production environments. Explore innovative modeling techniques in the realm of machine learning for systems. Contribute to the wider AI community by publishing research, presenting at conferences, and actively engaging in open-source projects, thereby strengthening Databricks' reputation as an industry leader.

The Senior Machine Learning Engineer at Scale AI is tasked with harnessing advanced methodologies in generative AI, computer vision, reinforcement learning, and agentic AI to enhance our product offerings and streamline the customer experience in live environments. Our machine learning engineers utilize a robust internal infrastructure and unparalleled access to extensive datasets to drive significant improvements for our clients. As part of the Public Sector Machine Learning team, you will be at the forefront of deploying innovative models to critical government systems through groundbreaking products such as Donovan and Thunderforge. Our work encompasses various modalities, with a strong emphasis on large language models and computer vision. On the LLM front, we are developing sophisticated agentic systems designed to address intricate operational and planning challenges for government entities. This involves creating agent frameworks that interface with custom retrieval systems and production APIs, alongside evaluation tools for assessing and refining agent performance. Additionally, we are pioneering research in reinforcement learning for agentic LLMs, successfully deploying these innovations in real-world operational contexts. In the realm of computer vision, we are focused on training advanced models to boost labeling throughput and automate perception tasks. Our initiatives include developing large-scale fine-tuning pipelines, training models across diverse modalities, and creating adaptable vision foundation models to support a variety of defense applications.

Join Arcade as a Senior Machine Learning Engineer, where you'll be at the forefront of AI innovation. In this pivotal role, you will leverage advanced machine learning algorithms to create and enhance cutting-edge solutions. Collaborate closely with cross-functional teams to drive impactful projects from ideation to deployment.

Our MissionAt Altos Labs, we are dedicated to revitalizing cell health and resilience through innovative cell rejuvenation techniques to reverse disease, injury, and the disabilities that arise throughout life.Discover more about our vision at altoslabs.com.Our ValuesOur core value is simple yet powerful: Everyone Owns Achieving Our Inspiring Mission.Diversity at AltosWe understand that diverse perspectives are crucial for scientific breakthroughs and exploration. At Altos, exceptional scientists and industry leaders collaborate from around the globe to drive our shared mission forward. We prioritize a culture of belonging, ensuring that every employee feels valued for their unique contributions. We are all responsible for maintaining a diverse and inclusive workplace.Your Contributions to AltosJoin Altos Labs in creating a premier AI ecosystem aimed at addressing the most intricate challenges in human biology. You will be instrumental in designing and developing high-performance, scalable solutions that integrate high-dimensional biomedical imaging with molecular and linguistic data.Your role will involve implementing large-scale multimodal data fusion, advancing beyond basic image analysis to develop predictive models that span various biological domains. You will engage directly with data and coding, partnering with our engineering team to ensure these models are scalable, efficiently trainable in distributed cloud environments, and accessible to our global research network.Key ResponsibilitiesModel Development: Create, implement, and train large-scale foundational models (e.g., Vision Transformers, Multimodal LLMs) capable of embedding spatial data and integrating diverse modalities.Innovative Data Fusion: Apply cutting-edge cross-domain mapping and fusion techniques to align heterogeneous biological datasets.Scaling & Training: Develop and oversee high-performance ML pipelines designed to handle petabyte-scale image collections and multi-omics data streams in a cloud infrastructure.Technical Collaboration: Work closely with experimental scientists and software engineers to convert biological complexity into high-performance code and reliable distributed systems.Who You AreWe seek a technical expert who excels at unraveling "unsolvable" challenges through programming and meticulous experimentation. We welcome candidates at the Scientist I, Scientist II, or Senior Scientist levels.

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.