Design, implement, and maintain robust, containerized, and reproducible pipelines for model training, evaluation, and deployment—across both batch and real-time settings.
Build and manage ML services, APIs, and model serving infrastructure using tools like MLflow, Amazon SageMaker, and Feature Store.
Set up and maintain monitoring, observability, and alerting systems to ensure high availability and performance (including model/data drift, feature logging, and inference latency).
AUTO1 Group Technology drives innovation in the used car market across Europe. They operate at the intersection of software engineering, data science, and DevOps, helping bring state-of-the-art ML models—such as large-scale recommendation systems and transformer-based neural networks—safely into production.
Own the end-to-end lifecycle of ML model deployment—from training artifacts to production inference services.
Design, build, and maintain scalable inference pipelines using modern orchestration frameworks (e.g., Kubeflow, Airflow, Ray, MLflow).
Implement and optimize model serving infrastructure for latency, throughput, and cost efficiency across GPU and CPU clusters.
MARA is building a modular platform that unifies IaaS, PaaS, and SaaS which will enable governments, enterprises, and AI innovators to deploy, scale, and govern workloads across data centers, edge environments, and sovereign clouds. They are redefining the future of sovereign, energy-aware AI infrastructure.
Design, develop, and deploy robust ML systems and multi-model AI agents that solve real-world retail challenges.
Lead the entire lifecycle, including prototyping, deployment, monitoring, and maintenance using modern CI/CD and containerisation practices.
Build high-performance data pipelines (ETL/ELT) for both training and real-time inference, ensuring our systems are scalable and reliable.
EDITED is the world’s leading AI-driven retail intelligence platform. They empower the world’s most successful brands and retailers with real-time decision making power. Their environment is dynamic and supportive, encouraging team members to take initiative, innovate, and continuously grow.
Manage, mentor, hire and grow 8+ ML Engineers and Data Engineers across three distinct teams
Be a strong technical partner for engineers to guide ML system architecture, model deployment, and data platform design & execution
Ensure ML solutions are production-grade, scalable, observable, cost effective and maintainable
Apella is applying computer vision and machine learning to improve the standard of care in surgery. They build applications to enable surgeons, nurses, and hospital administrators to deliver the highest quality care; they are committed to equal employment opportunity.
Take ownership of an ML deployment system spanning multiple production environments and continue to research efficient and effective strategies.
Improve, expand, and streamline our existing deployment pipelines to support faster deployments and automated model retraining.
Collaborate with Data Scientists to understand model requirements and provide guidance to ensure seamless integration with production environments.
Best Egg is a market-leading, tech-enabled financial platform helping people build financial confidence through lending solutions and financial health tools. They foster an inclusive, flexible, and fun workplace with top-tier benefits and growth opportunities.
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.
Design, develop, and deploy AI/ML models and pipelines that meet mission and performance objectives.
Build, train, and fine-tune models using frameworks such as PyTorch, TensorFlow, scikit-learn, Hugging Face, and LangChain.
Write clean, efficient Python code for data ingestion, feature engineering, embeddings, and inference services.
Frontier Technology Inc. (FTI) delivers mission-focused solutions to the Department of Defense (DoD/DoW) and Intelligence Community (IC) through advanced engineering, digital transformation, and program execution expertise. They help their customers solve complex challenges and achieve mission success by integrating people, process, and technology.
Implement production AI / ML workloads using Ray and Anyscale.
Advise customers on ML system architecture.
Partner with customer MLE and MLOps teams to integrate Ray into existing platforms and workflows.
Anyscale is on a mission to democratize distributed computing and make it accessible to software developers. They are commercializing Ray, an open-source project creating an ecosystem of libraries for scalable machine learning and are backed by Andreessen Horowitz, NEA, and Addition.
Develop scalable MLOps pipelines for model training, validation, deployment, and monitoring using AWS services
Implement infrastructure as code and CI/CD workflows to support rapid experimentation and reliable production releases
Collaborate with data scientists to productionize ML models and ensure reproducibility, versioning, and traceability
Experian is a global data and technology company, powering opportunities for people and businesses around the world. A FTSE 100 Index company listed on the London Stock Exchange (EXPN), they have a team of 23,300 people across 32 countries and corporate headquarters are in Dublin, Ireland.
Own deployment engineering projects, leading the technical execution of Parloa’s deployments inside large, complex enterprise environments.
Design for scale and resilience, architecting deployment solutions that meet enterprise-grade requirements for performance, reliability, and security.
Engineer solutions where none exist, building custom extensions, integrations, and configurations to close product gaps and meet enterprise requirements.
Parloa is a fast-growing startup in the world of Generative AI and customer service. Their voice-first GenAI platform automates customer service with natural-sounding conversations and has over 400+ employees in Berlin, Munich, and New York.
Prototype new training frameworks and production-ize solutions at scale.
Design, optimize and test model integration infrastructure.
Clarifai is a leading, full-lifecycle deep learning AI platform for computer vision, natural language processing, LLM's and audio recognition. Clarifai was founded in 2013 and has employees remotely based throughout the United States, Canada, Argentina, India and Estonia.
Work with research teams to design and build our training infrastructure
Prototype new training frameworks and production-ize solutions at scale
Design, optimize and test model integration infrastructure
Clarifai is a leading AI platform specializing in computer vision, NLP, LLMs, and audio recognition, helping organizations transform unstructured data into structured data. Founded in 2013, they remotely operate across multiple countries with backing from industry leaders, fostering a diverse and equal opportunity workplace.
Implement AI governance policies in collaboration with NBCU Legal, Privacy, and Cyber teams.
Build monitoring and reporting frameworks for AI models and tools, emphasizing cost, tagging, and AI FinOps principles.
Develop and manage ML/AI Ops pipelines including CI/CD for models using GitHub Actions or Jenkins.
NBCUniversal is a media and entertainment company that creates world-class content distributed across film, television, and streaming. They also have global theme park destinations, consumer products, and experiences. NBCUniversal is a subsidiary of Comcast Corporation, and it strives to attract and develop a talented workforce that reflects our world by championing an inclusive culture.
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.
Design, build, and scale enterprise-grade AI/ML systems that power internal workflows and external-facing AI/ML platforms.
Develop a production-ready Generative AI and MLOps platform with reusable components used to deploy multiple AI solutions across Natera’s business units.
Implement cloud-native infrastructure for large-scale model training and serving using Kubernetes, MLflow, Terraform, and AWS-native services
Natera is a global leader in cell-free DNA (cfDNA) testing. They are dedicated to oncology, women’s health, and organ health, aiming to make personalized genetic testing and diagnostics part of the standard of care. The Natera team consists of highly dedicated statisticians, geneticists, doctors, laboratory scientists, business professionals, software engineers and many other professionals from world-class institutions.
Work side by side with clients, PMs, and Architects to scope and deploy AI systems.
Build and integrate systems using LLMs, RAG pipelines, agent frameworks, vector databases and related tools.
Debug relentlessly and optimize for reliability in production, not just elegance in code.
Jobgether uses an AI-powered matching process to ensure your application is reviewed quickly, objectively, and fairly against the role's core requirements. Their system identifies the top-fitting candidates, and this shortlist is then shared directly with the hiring company.
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, develop, and deploy machine learning models and pipelines using Python
Build and maintain end-to-end ML systems from data ingestion to model serving
Write clean, efficient, and maintainable Python code following best practices
Activate Group was named by the Sunday Times as one of the UK’s 100 fastest-growing private companies. They employ more than 700 team members nationwide and work with some of the UK's largest fleets and insurance companies, supporting drivers involved in road incidents.
Design and deliver scalable AI systems that connect models, data, and products.
Turn research prototypes into secure, reliable, production-ready services.
Build pipelines and serving layers that power adaptive, real-time features.
KnowBe4 is a cybersecurity company that puts security first, offering an AI-driven Human Risk Management platform. They empower over 70,000 organizations worldwide to strengthen their security culture and transform their workforce into their strongest security asset.