Source Job

Participate in the design, maintenance, and improvement of Torc's AA frameworks. Work with cloud tools like Terraform, AWS Managed Services, and EKS. Build solutions for AA that have reached the production stage.

Torc, a leader in autonomous driving since 2007 and now part of the Daimler family, focuses on developing software for automated trucks to transform freight transportation.

• Design and implement production-grade auto-labeling pipelines that generate 3D and 4D annotations from multi-modal robot data at scale.
• Develop data-centric learning workflows that connect auto-label outputs, Serve’s dataset infrastructure, and continuous E2E model training and evaluation pipelines.
• Lead initiatives in self-training, weak supervision, and simulation-to-real adaptation to reduce manual labeling dependency and accelerate model iteration cycles.

Serve Robotics is reimagining how things move in cities with their sidewalk robot designed to take deliveries away from congested streets and benefit local businesses.

Lead AI and ML initiatives to design and implement production-grade machine learning systems and pipelines. Develop scalable infrastructure for model training, evaluation, and deployment, ensuring reliability and observability. Collaborate with cross-functional teams to drive innovation and efficiency.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

• Define the vision and feature set for our internal Robotics Data Platform.
• Act as the Product Owner for a dedicated team of software engineers.
• Participating in discussions with leading robotics labs and foundation model builders.

Turing is the world’s leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Recognized by Forbes, The Information, and Fast Company among the world’s top innovators, Turing’s leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT.

• Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows.
• Develop full-stack tooling and backend services for large-scale data annotation, validation, and quality control.
• Improve reliability, performance, and safety across existing Python codebases.

Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.

• Develop and optimize computer vision algorithms for road model detection.
• Design and implement deep learning models for road model inference in BEV frameworks.
• Collaborate with robotics, software, and hardware engineering teams for seamless integration.

Torc has been a leader in autonomous driving since 2007, commercializing solutions with experienced partners and now focused on developing software for automated trucks.

• Lead development of models for autonomous vehicles to perceive and interpret road geometry.
• Define next-generation deep learning architectures for extracting road and lane semantics from sensor data.
• Develop evaluation frameworks for lane and road geometry accuracy and cross-domain generalization.

Torc has been a leader in autonomous driving since 2007 and is now part of the Daimler family, focusing solely on software development for automated trucks.

• Build, maintain and improve Torc ML frameworks.
• Use Terraform, AWS Managed Services, EKS, Ray.
• Focus on data ops, ML development pipeline, logging & aggregation.

Torc has been a leader in autonomous driving since 2007. Now a part of the Daimler family, they are focused solely on developing software for automated trucks to transform how the world moves freight. Their culture is collaborative, energetic, and team focused.

• Design scalable, future-proof data platforms optimized for AI research workloads.
• Build efficient self-serve data processing pipelines leveraging GCP's advanced services.
• Implement guardrails for cost, quality, and performance.

AssemblyAI is at the forefront of Speech AI, creating powerful models for speech-to-text and speech understanding via an API. They're a remote team of startup veterans and AI researchers looking to build one of the next great AI companies.

• Develop machine learning models that interpret and predict road and lane structures.
• Work with multi-modal sensor data, including cameras, LiDAR, and radar, to create 3D representations of driving surfaces.
• Optimize algorithms for real-world deployment, influencing vehicle navigation and safety.

We use an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements.

• Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
• Improve reliability, performance, and safety across existing Python codebases

Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.

• Evolve and support real-time machine learning/AI pipelines to build low-latency, high-throughput systems.
• Design and implement cloud solutions using AWS to ensure high performance, scalability, and reliability.
• Guarantee high levels of service availability through being a part of an on-call rotation, following best practices for disaster recovery and business continuity.

Sony Interactive Entertainment (SIE) PlayStation creates unforgettable gaming experiences and is dedicated to building a world-class team.

• Operationalize data science solutions for risk-prediction products.
• Design and build ML pipelines using AWS services and tools like MLflow and Snowflake.
• Implement testing strategies within CI/CD pipelines to maintain high platform quality.

Quanata is on a mission to help ensure a better world through context-based insurance solutions.

• Implement data science and machine learning solutions to optimize internal operations and SaaS products.
• Communicate methods and findings with stakeholders through reports, presentations, dashboards, and APIs.
• Build machine learning models and deploy them as production services at scale.

GoGuardian is an outcomes-focused learning company with a steadfast focus on improving learning environments, one classroom at a time.

Deploy and monitor machine learning models in production using tools like Docker, Kubernetes, and MLflow to ensure scalability and reliability. Build and maintain data pipelines using Airflow, Spark, or Kafka to support model training and inference. Integrate ML models into business applications, collaborating with software engineers to operationalize solutions.

Jobgether is a Talent Matching Platform that partners with companies worldwide to efficiently connect top talent with the right opportunities through AI-driven job matching.

• Help define the direction for the team.
• Define and prioritize ML Platform initiatives.
• Enable teams to build features at scale by providing a foundation of reusable software components and infrastructure.

Motive empowers the people who run physical operations with tools to make their work safer, more productive, and more profitable. Motive serves nearly 100,000 customers – from Fortune 500 enterprises to small businesses – across a wide range of industries.

• Design, build, and optimize high-performance systems in Python supporting AI data pipelines and evaluation workflows
• Develop full-stack tooling and backend services for large-scale data annotation , validation, and quality control
• Improve reliability, performance, and safety across existing Python codebases

Alignerr connects top technical experts with leading AI labs to build, evaluate, and improve next-generation models. They work on real production systems and high-impact research workflows across data, tooling, and infrastructure.

• Build and deploy AI-driven products that accelerate clinical trials and improve patient outcomes.
• Develop advanced ML models and LLM-powered agents for critical use cases like patient recruitment, enrollment forecasting, and study feasibility.
• Leverage modern cloud tools and MLOps best practices to build robust data pipelines and deploy models at scale.

At OneStudyTeam (a Reify Health company), we specialize in speeding up clinical trials and increasing the chance of new therapies being approved with the ultimate goal of improving patient outcomes.