Machine Learning Engineer

Join Our Team at RebarRebar is revolutionizing the operating systems used by commercial HVAC, electrical, and plumbing suppliers and subcontractors. In the past year, our initial quoting product has successfully scaled to processing thousands of quotes weekly, and we've doubled our revenue in 2026 while gaining traction among top suppliers across North America. Fresh from securing a $14M Series A investment from leading construction technology investors, we are poised for our next growth phase with AI at the core of our innovations.We are seeking a Principal Deep Learning Engineer who possesses a strong background in modern neural network techniques and proficiency in PyTorch. You will be instrumental in advancing computer vision applications in real-world settings. As part of a tight-knit, highly skilled team, you will focus on delivering practical, production-ready machine learning systems—from building data pipelines to developing finely-tuned models—within a dynamic startup environment.This position is ideal for individuals who thrive on working closely with models, refining training workflows, and tackling novel engineering challenges. Our work transcends mere model inference; we create training workflows, develop robust evaluation pipelines, and construct systems that enhance standard model usage.

Join Our Innovative TeamBecome a pivotal member of our team dedicated to creating the world's first biological reasoning model. Collaborate with us on groundbreaking generative foundational models that interpret biological systems across various scales—from molecular interactions to entire organisms—empowering us to predict, comprehend, and manipulate living systems like never before.Output is currently in stealth mode, driven by a team of seasoned founders and biotech experts who have successfully exited ventures in AI and biotechnology, supported by leading venture capital firms including Y Combinator.As a Machine Learning Engineer, you will partner with our founders and talented team members to innovate and deploy advanced AI solutions that facilitate intricate biological reasoning across diverse scales.Develop foundational models for biological systems capable of encoding and decoding biological data at scale.Create deep generative models tailored for biological applications, experimenting with innovative architectures to capture the complexities of multi-scale biological systems.Work on distributed training systems to scale our models to billions of parameters, focusing on performance and efficiency across multi-GPU and multi-node configurations while processing extensive biological datasets.Design efficient data pipelines to manage and process large biological datasets, tackling challenges in data loading, partitioning, and memory optimization.Establish and implement robust evaluation frameworks for complex biological models, ensuring data integrity and preventing leakage across dataset splits.

Join our dynamic team at Blacksmith as a Principal Systems Engineer, where you will play a crucial role in designing, developing, and implementing innovative systems solutions. Your expertise will guide projects from conception to execution, ensuring they meet both technical and user requirements.

P-1125 Summary At Databricks, we are dedicated to empowering data teams to tackle the most challenging issues facing the world today, from detecting security threats to developing cancer treatments. Our mission is to create and maintain the premier data and AI infrastructure platform, allowing our clients to concentrate on the critical challenges central to their objectives. Our engineering teams are at the forefront of innovation, delivering highly sophisticated products that meet significant global demands. We relentlessly push the limits of data and AI technology while ensuring the resilience, security, and scalability essential for our customers’ success on our platform. Trust is paramount at Databricks, and our Trust & Safety initiative is dedicated to establishing the most reliable data analytics and machine learning platform globally. Security Engineering plays a crucial role in protecting customer data from malicious threats. We seek experienced leaders like you to craft the vision and outline the strategy in this vital area.

About AlphaSense: AlphaSense empowers the world's leading companies to eliminate uncertainty in decision-making. Our platform, founded on advanced AI technology, delivers essential insights from both public and private content, including equity research, company filings, event transcripts, expert calls, news, trade journals, and proprietary research. In 2024, AlphaSense enhanced its mission by acquiring Tegus, furthering our goal to provide professionals with AI-driven market intelligence. This collaboration will accelerate our growth and innovation, combining our product and content offerings to deliver even deeper insights from a wealth of information. Trusted by over 6,000 enterprise clients, including a majority of the S&P 500, AlphaSense has been at the forefront of market intelligence since its inception in 2011. Headquartered in New York City, we have grown to over 2,000 employees globally, with offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Join us on this exciting journey!About the Team:Our dynamic Product & Engineering team thrives on innovation, collaboration, and continuous enhancement of our platform. We foster an engaging work environment that encourages personal and professional growth while developing pioneering technology that shapes the future of AI and search.At AlphaSense, we value diverse backgrounds and perspectives as vital to our success. We are dedicated to fostering an inclusive workplace where every employee feels respected and empowered to express their authentic selves.About the Role: We are on the lookout for a Principal Engineer to spearhead the design, evolution, and reliability of our global financial data extraction and normalization platform. This system processes filings in various formats (HTML, PDF, APIs, spreadsheets), utilizes a mix of AI and deterministic methods to extract and standardize financial data, and delivers reliable, traceable outputs at scale to financial services teams and customers.In this role, you will own the self-sourcing and extraction foundation utilized by multiple teams across the organization. Currently, human validation acts as a safeguard. Your objective is to systematically diminish human reliance by enhancing system accuracy, confidence, and trust, without compromising speed or scalability.

At Garner Health, we are dedicated to revolutionizing the healthcare economy by making high-quality and affordable care accessible to all.We are fundamentally reimagining the healthcare landscape in the U.S. by collaborating with employers to redesign healthcare benefits using transparent incentives and powerful, data-driven insights. Our innovative approach directs employees toward higher-quality, lower-cost care, fostering a healthcare system that benefits everyone. This means improved health outcomes for patients, more effective spending of healthcare dollars for employers, and rewarding physicians for providing exceptional care rather than performing unnecessary procedures.Garner is recognized as one of the fastest-growing healthcare technology companies nationally. Our products are trusted by the most sophisticated employers and providers in the industry, and we are building a team of talented, mission-driven individuals who are eager to make a significant impact on healthcare at scale.About the Role:We are on the lookout for an outstanding Staff Machine Learning Engineer to join our dynamic team. At Garner, our Engineering team addresses complex technical challenges that have a meaningful impact on our mission. Our systems analyze billions of medical records to evaluate healthcare providers nationwide. We operate on AWS with Kubernetes and consistently integrate new technologies as our system load grows exponentially each year. We encourage our engineers to advocate for cutting-edge industry practices as we wholeheartedly incorporate AI into every aspect of our operations and standards. We value teammates who take pride in delivering exceptional work and nurturing a robust team culture.Where You Will Work:This position is based in our New York City office located in the Financial District. Candidates must be available to work in the office three days a week: Tuesday, Wednesday, and Thursday.What You Will Do:Lead technical strategy and execution at the team level over multi-quarter time frames.Utilize AI to build, optimize, and maintain machine learning, data, and software systems.Elevate the technical capabilities of engineers throughout the organization.Collaborate across disciplines to deepen domain understanding and iterate on projects.Ensure user privacy and security through adherence to best practices.

Nagarro is seeking a Principal Engineer focused on AI Architecture in New York City. This position centers on designing and implementing advanced AI solutions to support business transformation. Role overview The Principal Engineer will work closely with cross-functional teams to develop scalable AI architectures. Responsibilities include guiding the design process, ensuring strong development practices, and supporting strategic initiatives across the organization. What you will do Lead the creation and rollout of AI-driven solutions Collaborate with teams to ensure scalable and maintainable architectures Promote best practices in AI development Support projects that enhance the efficiency and impact of Nagarro’s services Requirements Deep expertise in AI technologies and architecture Experience designing and implementing AI solutions Strong collaboration skills with technical and non-technical teams

About UsAt globaledit, a proud division of CoCreativ, we lead the charge in providing an innovative SaaS platform designed to enhance the efficiency and speed of creative production. Backed by private equity, our operations span New York City and Los Angeles, and we are privileged to serve a prestigious client roster, including renowned fashion brands, retailers, and entertainment giants like Morphe Cosmetics, Rag and Bone, and Warner Bros. This position offers a hybrid work model, requiring you to be onsite in our Tribeca office three days a week.The RoleWe are on the lookout for a technical visionary with a proven track record of execution. You will join a dynamic team of 14 engineers, tasked with building and scaling a serverless platform that supports creative workflows for our major clients.This role is hands-on and focuses on practical contributions rather than prolonged meetings. You will immerse yourself in the code, make architectural decisions, mentor team members, and drive feature development. Collaborating closely with Product, you will bring a technical perspective to product prioritization and planning.Your team enjoys a high degree of autonomy. Your role will involve setting the strategic direction, eliminating obstacles, and ensuring that we are addressing the right challenges effectively. We seek someone who can harmonize the need for speed with the necessity of stability.What You'll DoBuild and ShipMake pivotal architectural decisions for our serverless platform – you will define the technical trajectory.Conduct code reviews, challenge different approaches, and guide the team towards optimal solutions.Dive into significant technical challenges and proactively engage with the code.Identify and remedy issues that are hindering our progress (such as tech debt, processes, or tools).Drive ResultsCollaborate with Product to convert requirements into actionable builds.Monitor AWS costs and performance metrics vigilantly.Our StackWe utilize a cutting-edge, serverless architecture on AWS, including:Backend: C#/.NET on Lambda, API Gateway, and Step Functions.Frontend: React deployed on S3/CloudFront.Infrastructure: CloudFormation for Infrastructure as Code (IaC).Tooling: Azure DevOps for repositories, pipelines, and project management.Additional: An Electron desktop app, a React Native iOS app, and a Photoshop plugin (maintained but not frequently updated).If you are well-versed in AWS serverless technologies and have experience with similar tools, you will thrive in this environment. We do not expect you to be familiar with every tool from day one.

Doppel seeks a Principal Sales Engineer to support sales efforts across the Northeast region. This remote position is based in New York City and centers on helping clients succeed with Doppel’s online identity protection technology. Technical expertise guides both the product and the way the team serves customers. Role overview This role partners with Account Executives to understand customer goals and challenges. The Principal Sales Engineer develops solutions tailored to each client, ensuring Doppel’s offerings address specific needs. Key responsibilities Collaborate with Account Executives to identify and analyze customer requirements Create and present solutions that align with client objectives Explain technical concepts in clear, business-focused terms Lead technical activities from discovery through demonstrations, proposals, and implementation Foster trust and maintain transparency in all client interactions About Doppel Doppel develops technology to protect online identities. The team values technical skill and a mission-driven mindset, supporting clients as they adopt and expand their use of Doppel’s solutions.

Join our dynamic team at Nagarro as an Associate Principal Engineer - Project Manager. In this pivotal role, you will lead engineering projects, ensuring timely delivery and adherence to quality standards. You will collaborate with cross-functional teams to drive innovation and efficiency while mentoring junior engineers to foster professional growth.

About Our TeamThe Education team at OpenAI is dedicated to creating systems that transform ChatGPT into a powerful learning ally. As advancements in AI unfold rapidly, we aim to develop educational tools that empower individuals, educators, developers, and organizations to progress from curiosity to expertise with the aid of AI technologies.Our team operates at the crossroads of artificial intelligence, educational psychology, and large-scale platforms, building the foundation for AI-driven learning experiences worldwide.About the RoleWe are looking for a Learning Systems Engineer to join us in establishing the infrastructure that supports AI-enhanced educational experiences. This role integrates backend architecture, learning science, research, and product development.You will convert educational objectives into scalable systems: learner models, tracking progress, adaptive feedback mechanisms, formative assessments, and analytics that demonstrate effective learning outcomes.Your contributions will help millions globally learn efficiently and harness the full potential of AI.What You Will Work OnDevelop AI-Driven Learning Infrastructure: Create essential systems for AI education, including dynamic learning experiences, progress tracking, and assessments.Facilitate Adaptive Learning: Design capabilities that enable learning experiences to evolve according to learners’ knowledge, goals, and behaviors over time.Construct Data Systems for Insights: Develop data pipelines and analytical systems that help educators grasp learner outcomes, engagement trends, and skill advancement.Empower Educators: Create systems that allow non-technical users to design, configure, and experiment with learning experiences without needing direct engineering assistance.First 12 Months Success IndicatorsLaunch innovative AI learning experiences that cater to a diverse range of learners.Enhance infrastructure that enables educators to offer adaptive learning and assessments.Validate the learning analytics pipeline for deeper insights into AI-driven education.Enable education teams to leverage AI tools for scalable development and iteration.

About TennrAt Tennr, we are transforming the way healthcare referrals are managed. When patients are referred to specialists, they often face frustrating delays. Our innovative platform, powered by RaeLM™, ensures that every referral is processed swiftly and accurately, allowing healthcare providers to capture more referrals and reduce denials. Join us in revolutionizing the healthcare experience.About the RoleAs the pioneering ML Ops Engineer at Tennr, you will be instrumental in developing and refining our Machine Learning and AI infrastructure. You will be responsible for creating and optimizing machine learning training and inference pipelines that can manage escalating traffic demands and an expanding range of products. Your expertise will ensure that our AI-driven healthcare platform operates on robust, scalable, and efficiently deployed models.Our Machine Learning team is at the forefront of innovation, developing proprietary VLMs, LLMs, and other specialized models tailored to address critical healthcare challenges. This is not just a position of maintaining existing systems; it is an opportunity to lead groundbreaking experimentation and the introduction of new capabilities. Your contributions will significantly impact our ML and data systems, enhancing Tennr's ability to solve vital issues for patients and healthcare providers.Key ResponsibilitiesDesign, architect, and implement scalable ML software systems for model deployment and management.Maintain infrastructure that supports efficient ML operations, including data pipelines, model evaluations, and large-scale training.Work collaboratively with ML engineers, software developers, and cross-functional teams to integrate models seamlessly with data pipelines and products.Identify and resolve production issues while continuously enhancing system performance and efficiency.Develop tools for online and offline evaluation of ML and LLM systems.

About General IntuitionGeneral Intuition is at the cutting edge of AI research, dedicated to developing foundational models that excel in deep spatial and temporal reasoning. Over the past year, we have advanced the capabilities of AI agents that navigate complex environments, created world models that serve as training grounds for these agents, and innovated video understanding models aimed at real-world application.We are proud to have raised a seed funding round of $133 million from General Catalyst and Khosla, driving our mission to uncover the next generation of intelligence.What We're Looking ForMinimum of 5 years of experience in deep learning research or reinforcement learning, specifically with embodied agents or simulation environments.Solid foundation in representation learning and generative modeling, particularly using architectures like diffusion models, VAEs, and transformers applied to video data.Experience with world models and predictive control — you possess knowledge on training models that simulate dynamics and plan actions within learned environments.Proficiency in reinforcement learning (RL, model-based RL, or imitation learning), coupled with the capability to design and evaluate policy networks.Excellent programming skills in Python and deep learning frameworks such as PyTorch.Strong experimental capabilities — adept in handling large-scale training, evaluation pipelines, and managing intricate datasets or simulations.Publications or contributions to open-source projects in domains such as world modeling, simulation learning, or agent policies are a significant advantage.In-person requirement: We are specifically seeking candidates located in New York City, with a commitment to working in the office five days a week.Ownership & scientific rigor: You are committed to seeing ideas through from conception to proof of concept to deployment. You write clean, reproducible code and uphold high standards for experimental validity.Performance and scaling mindset: You understand how research can be translated into production systems, with a keen awareness of compute efficiency, distributed training, and potential data bottlenecks.Curiosity-driven and results-oriented: You thrive on tackling open-ended problems, while also knowing how to set measurable goals and deliver impactful systems.Passion for gaming & simulation: A strong interest in interactive environments and physics-based simulations is highly desirable.

Trunk Tools seeks a Senior Machine Learning Engineer to join its team onsite in New York City. This role centers on creating and deploying models that drive the company’s main objectives. Working alongside colleagues from various backgrounds is a key part of the job. Responsibilities Design and build machine learning models for practical use cases Collaborate with cross-functional teams to gather requirements and deliver effective solutions Deploy models into production environments and monitor their scalability Work Location This position is based at the Trunk Tools headquarters in New York City. Regular onsite presence is required.

Join Our Team as a Machine Learning Engineer! At FanDuel, we recognize that data is the lifeblood of our organization. As a Machine Learning Engineer, you will harness the power of our extensive real-time and relational datasets to drive insights that enhance user experiences. Your analytical skills will transform every interaction—from user clicks to game outcomes—into actionable intelligence, enabling us to make faster, more informed decisions that keep us ahead of the competition. Your role will be pivotal in fostering collaboration across teams. You will serve as the bridge between engineering teams, facilitating the development of our online applications while ensuring that essential data is available for feature engineering. Collaborating with Data Scientists and Analysts, you will help bring AI-driven insights into production and validate their effectiveness. Your efforts will be instrumental in organizing, modeling, and presenting data in a manner that provides a unified information structure, empowering FanDuel to respond intelligently to market dynamics and on-field events. If you are a Machine Learning Engineer with aspirations to thrive in a big data environment, we encourage you to apply! Your Responsibilities: Design and implement intelligent search systems incorporating typeahead search, vector search, and ML personalization to optimize user experience. Contribute to the creation of scalable serving systems for ML and GenAI/LLM models. Develop platform features and tools (e.g., CLI, SDK, Infrastructure Automation) that enhance the ML model lifecycle and GenAI/LLM application deployment. Utilize business intelligence tools such as Tableau, Knime, and Looker. Ensure data security and privacy compliance (e.g., GDPR, CPP). Implement data governance and testing frameworks. Support continuous integration and delivery of data products. Participate in an inclusive culture that prioritizes excellence, personal growth, and well-being.

About SandbarSandbar is a pioneering interface company based in New York City, dedicated to enhancing individual autonomy in an agentic world. Our team comprises experts who have developed cutting-edge software, machine learning, and hardware products at renowned companies like Meta, CTRL-labs, Google, Apple, Fitbit, Peloton, and Equinox.Our flagship product, Stream, represents a revolutionary human-agent interface—a private voice ring and conversational computer. This innovative product has received accolades in major publications such as the Wall Street Journal, Bloomberg, and Wired, with shipping scheduled for Summer '26.Join us in redefining self-augmentation through advanced interfaces.

OverviewAt OXMAN, a pioneering nature-focused research and design firm based in Manhattan, we leverage nature-centric solutions to tackle pressing challenges at the intersection of Nature and Humanity. Our interdisciplinary approach spans various sectors, fostering innovative concepts that redefine the interaction between the built environment and the natural ecosystem.Our initiative, EDEN, is dedicated to applied ecological systems operating on architectural, urban, and landscape scales. We are at the forefront of creating a digital design framework that engineers biodiverse and resilient ecosystems by developing software that empowers designers and engineers to incorporate essential ecosystem services—such as carbon sequestration, thermal buffering, and biodiversity—into their master planning and design processes. Our mission is to elevate ecosystem services from undervalued byproducts to vital infrastructure elements. We invite talented professionals to join us in revolutionizing the future of nature-centric design.We are currently seeking a Machine Learning Research Engineer to integrate into our dynamic design team in New York City. This role will be pivotal in supporting our efforts to deliver exceptional, data-driven design proposals utilizing EDEN’s innovative suite of ecosystem engineering tools.

At Confido, we are revolutionizing the AI infrastructure for consumer packaged goods (CPG) brands, streamlining everything from deductions to production planning. Our platform integrates cash applications, deductions, disputes, trade promotion management, forecasting, demand planning, and analytics into a cohesive system. The outcome is significant time savings, enhanced decision-making capabilities, and accelerated growth potential.We proudly serve over 200 brands, managing more than $20 billion in revenue, with clients like OLIPOP, Simple Mills, Dr. Squatch, and Tropicana.With our recent successful $15 million Series A funding round led by Footwork Ventures and Y Combinator, we are poised for rapid expansion.As a Staff AI / ML Engineer, you will play a crucial role in developing and implementing the core AI systems that power our platform, including LLM-driven document understanding and predictive models that assist brands in making informed decisions.This foundational position will involve direct collaboration with our CEO and CTO to define our long-term AI strategy and architecture.

About AlphaSense: AlphaSense is the go-to platform for the world’s leading companies seeking to eliminate uncertainty in decision-making. Leveraging advanced AI, our market intelligence and search capabilities provide crucial insights from reliable content. Our extensive database encompasses public and private materials such as equity research, company filings, event transcripts, expert calls, news articles, trade journals, and proprietary client research.The recent acquisition of Tegus by AlphaSense in 2024 enhances our shared mission to empower professionals through AI-driven market intelligence. Together, we aim to foster growth, innovation, and the expansion of diverse content offerings, equipping users to discover in-depth insights from a multitude of data sets. Trusted by over 6,000 enterprise clients, including a significant portion of the S&P 500, AlphaSense has been a pioneer since its inception in 2011, headquartered in New York City with a workforce of more than 2,000 across various global offices in the U.S., U.K., Finland, India, Singapore, Canada, and Ireland. Join our team today!About the Team:Our vibrant Product & Engineering team thrives on innovation, collaboration, and constantly enhancing our platform. We foster a dynamic work environment that encourages personal and professional growth while developing cutting-edge technology that defines the future of AI and search.At AlphaSense, we value diversity in experiences and perspectives, which we believe are essential to our success. We are dedicated to cultivating an inclusive workplace where every employee feels appreciated and empowered to express their true selves.About the Role: As a part of AlphaSense, the GenSearch system is a production-level, customer-facing generative AI solution that provides reliable answers across various domains. Our team is responsible for the financial data agent within GenSearch—integrating AI reasoning with structured financial datasets—and for the financial data web experiences that facilitate fundamentals, M&A, screening, and other key functionalities.We are seeking a proactive Principal Engineer to assist us in:Reducing latency in AI-powered financial responsesSimplifying complex and outdated architectureEnhancing cross-dataset querying and screeningDelivering new datasets and product capabilities without escalating systemic complexity