Source Job

• Lead ambitious research in computer vision, multimodal understanding, and visual generation.
• Bridge cutting-edge research to practical product improvements.
• Mentor scientists and set technical direction for high-impact AI.

Webflow is an agentic web marketing platform that helps marketing teams build, manage, and optimize high-performing web experiences. It is a fast-moving, growing company that values grit, craft, and quality, offering equity and comprehensive benefits.

• Build and improve ML models for classification, ranking, retrieval, and personalization.
• Develop efficient classifiers and optimize accuracy, precision, latency, and cost.
• Debug production issues and ship improvements based on real-world feedback.

• Owns the architectural direction for Code Metal's AI platform and the team building it.
• Builds production-grade inference serving, model gateways, agent harnesses, and context-engineering services.
• Instruments the stack end to end and drives experimentation and observability for reliable AI systems.

Code Metal provides automated software engineering using AI and formal verification to produce provably correct code. Founded in 2023 and backed by Accel, Salesforce Ventures, and others, it serves defense and enterprise customers from offices in Boston and San Francisco.

• Own end-to-end ML systems from data and training to evaluation, inference, and deployment.
• Build and evolve training, fine-tuning, and inference infrastructure for large models.
• Partner with research and application engineering to turn model capabilities into product improvements.

Next Step Systems is an IT recruiting and staffing agency that connects companies with machine learning and technology talent. They specialize in placing candidates in remote and on-site roles across the United States and emphasize a fast-paced, results-oriented culture.

• Design, build, and deploy production ML and LLM-based systems for enterprise clients
• Own technical delivery end-to-end, from architecture to deployment and monitoring
• Mentor junior ML engineers and shape internal best practices and tooling

TensorOps is a boutique AI consultancy that bridges strategy and execution, designing and shipping production-grade AI systems for enterprise clients. We are a 100% remote, fast-growing team that values autonomy, open communication, and continuous learning.

• Bridge data science and production by building MLOps pipelines.
• Develop scalable data processing solutions with Spark and Databricks.
• Productionize ML models and ensure reliability through monitoring.

This company powers the global digital audio advertising ecosystem, turning large-scale listener data into actionable insights for advertisers. It operates in a technically advanced, cross-functional environment with a culture centered on respect, equity, and professional development.

• Build and maintain internal CLIs, SDKs, and services in Python or Go for deploying and debugging AI agents.
• Deploy, scale, and tune LLM inference with vLLM, including GPU scheduling and cost/latency trade-offs.
• Own MLOps workflows, Kubernetes operators, and CI/CD to take AI agents from laptop to production.

Tessera Labs builds multi-agent AI systems that automate complex enterprise workflows across platforms like SAP, Salesforce, and Snowflake. Backed by Foundation Capital, the startup operates with extreme ownership and a fast-moving culture at the frontier of applied AI.

• Own LLM and VLM support on Metis and Europa AIPUs, from studying new models to shipping them in the Voyager SDK.
• Use AI coding agents daily to build, test, and verify your work, combining LLM/VLM knowledge with solid software engineering.
• Productize results into supported Voyager SDK features with stable APIs, tests, documentation, and release gates.

Axelera AI is a deep-tech company creating the next-generation AI platform to advance humanity and improve the world. They have raised $450M, employ 250+ people (60+ PhDs) across 21 countries, and foster an open, innovative, and inclusive culture.

• Lead the end-to-end machine learning lifecycle, from data preparation and model training to evaluation, inference, and deployment.
• Build and optimize scalable training, fine-tuning, and inference pipelines for large-scale models on GPU infrastructure.
• Establish production best practices for model quality, reliability, safety, and measurable performance improvements.

This company builds production-grade machine learning systems and large-scale GPU-powered inference pipelines. It is a fully remote team that values technical rigor, collaboration, and hands-on engineering.

• Build and own the Theia SDK in Python and C++ for real-time eye-tracking inference across desktop, mobile, embedded, and XR platforms.
• Design APIs and backend services for data ingestion, model serving, licensing, and customer integrations with a focus on reliability and security.
• Operate AWS cloud infrastructure with Kubernetes, CI/CD, and monitoring, and scale data pipelines processing millions of eye-tracking records.

HarmonEyes is the world's only open, AI-powered eye-tracking platform that identifies and predicts cognitive, emotional, and physical states from eye movements using any camera-based device. Backed by 60+ years of eye-tracking experience and the largest validated eye-tracking database with 14 million records, it serves leading organizations in technology, aviation, healthcare, and elite performance.

• Learn, maintain, and improve our synthetic data pipeline and automated training system.
• Take over a model and improve it with an agent loop that generates its own data.
• Build closed loops where agents train detectors, test against validation sets, and improve with little human input.

CVEDIA builds computer vision models and applications that run on server and edge hardware using synthetic data. We are a small, fully remote team that uses AI agents across the company.

• Build and operate ML infrastructure and platforms powering AI products.
• Design systems for model training, evaluation, deployment, inference, and experimentation.
• Optimize model serving and inference infrastructure for high-throughput, low-latency workloads.

• Lead two established Applied Machine Learning squads delivering computer vision and deep learning products for American football and ice hockey.
• Set high standards across engineering and data science, balancing model precision with speed and cost in cloud infrastructure.
• Partner cross-functionally with product and technical leaders to align roadmaps and deliver real-time insights to coaches.

Hudl builds video and data products that help coaches and athletes capture, analyze, and share game footage. We're a people-first company with a supportive, autonomous culture that's been recognized as one of the Top 100 Inspiring Workplaces.

• Lead three highly technical teams spanning machine learning engineering, computer vision, forecasting, and data platform.
• Ensure machine learning systems move reliably from research to production with measurable real-world impact.
• Manage, mentor, hire, and grow the department of engineers and data engineers across three distinct teams.

Apella Technology applies machine learning to surgical healthcare operations, using computer vision and forecasting to improve clinical workflows. The company fosters a remote culture and is an equal opportunity employer, encouraging diverse backgrounds to apply.

• Design, develop, and deploy AI/ML models for predictive analytics and business process automation.
• Build and optimize machine learning algorithms and data pipelines for enterprise integration.
• Collaborate with data engineers and business stakeholders to ensure model performance and alignment.

Fusion Consulting is a global Business and IT consultancy specialized in Life Sciences, partnering with leading pharma and healthcare companies. With 450+ employees and 25 offices, we focus on S4HANA, Data & Cloud, with a client-first and entrepreneurial culture.

• Design, build, and deploy production AI applications, copilots, retrieval systems, and agentic workflows.
• Develop backend services, APIs, and application architectures that integrate AI capabilities into enterprise systems.
• Deploy AI solutions into production with appropriate security, observability, monitoring, evaluation, and governance.

We are a market-leading data, AI, analytics, and operations research advisory and solution engineering firm. We help organizations design, build, and operationalize enterprise-grade data and AI platforms with production-grade engineering discipline.

• Own the deployment and production lifecycle of models powering product experiences and marketing workflows.
• Build and maintain feature pipelines, monitoring systems, and CI/CD infrastructure for real-time inference and model health.
• Collaborate with data scientists and product engineers to ship scalable ML solutions across both product and marketing use cases.

Ethos is a leading life insurance technology company on a mission to democratize access to life insurance and empower agents at scale. With a three-sided technology platform, Ethos is transforming the life insurance experience for consumers, agents, and carriers, and is publicly traded on Nasdaq.

• Implement, validate, and iterate on machine learning algorithms for weld perception tasks including point cloud registration and seam detection.
• Build and maintain data pipelines for training and evaluating perception models, spanning annotated 3D scan data and synthetic data generation.
• Integrate trained models into production ROS-based robotics services, ensuring low-latency inference and compatibility with deployed systems.

Path Robotics develops embodied intelligence AI systems that enable robots to adapt, learn, and perform real-world tasks, closing the skilled labor gap. The company is a team of intelligent, humble, and driven individuals working on hard problems to transform industrial automation.

• Serve as a primary technical consultant, leading end-to-end AI/ML project implementations with clients.
• Design, build, and maintain production-grade AI/ML pipelines, emphasizing CI/CD and advanced MLOps/AIOps practices.
• Architect end-to-end AI/ML systems and manage infrastructure using Docker, orchestrators, and Databricks lakehouse.

Mutt Data is a dynamic startup committed to crafting innovative systems using cutting-edge Big Data and Machine Learning technologies. We build modern Machine Learning systems for demand planning, budget forecasting, and custom AI solutions, fostering a data-nerd culture with values like ownership and a positive mindset.

• Design, build, and operate AWS infrastructure supporting ML models, AI tools, and event-driven integrations.
• Build reliable CDC pipelines and event-driven integrations with third-party systems like Salesforce and Braze.
• Implement observability, secure operations, and model monitoring for production ML and LLM systems.

National Debt Relief helps consumers resolve debt and has settled over $10 billion for 450,000 clients. It is a certified Great Place to Work known for a team-oriented culture and employee growth.