Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients.
Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration.
Mentor and support other ML engineers on the team with code reviews, technical guidance, and knowledge sharing.
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 team of 11+ people, partnering with unicorns and NASDAQ-listed companies, and have a culture of autonomy, open communication, and continuous learning.
Design, train, and ship ML systems for governance and security like anomaly detection and trust scoring.
Build data pipelines, model serving, evaluation frameworks, and feedback loops.
Set technical direction, own architecture, and help recruit and mentor as the team grows.
Docker provides developer tooling trusted by over 20 million monthly users and billions of container pulls. They are a globally distributed, remote-first team building tools for software delivery.
Build ML infrastructure for low-latency model deployment, distributed inference pipelines, and real-time telemetry.
Scale ranking systems by moving models from experimentation to production, optimizing latency and cost trade-offs.
Implement model CI/CD for automated versioning, canary releases, hot-swappable container rollouts, and zero-downtime rollbacks.
Sequen provides an integrated platform that pairs cutting-edge frontier ranking models with infrastructure to run them in production at sub-10ms latency and enterprise scale. They are a small, highly technical, early-stage team focused on turning recent AI advances into production-grade systems.
Build the software backbone for autonomous foundation models, including multimodal data pipelines and training workflows.
Implement and iterate on LLM, VLM, and VLA architectures, owning model code paths and inference runners.
Deliver production-grade serving tooling for low-latency operation and own systems from architecture to iteration.
We're building the next generation of ground transportation with advanced physical AI to simplify freight challenges. Our stealth team, founded by engineers who scaled autonomous driving, is developing a new vehicle platform and focuses on creating reliable real-time autonomous systems.
Own end-to-end Machine Learning (ML) system execution including data pipelines, training, and deployment.
Fine-tune and adapt models using state-of-the-art methods like LoRA and DPO.
Architect scalable inference systems and collaborate closely with application engineering.
This company develops advanced production-grade machine learning systems. The team is small and high-trust, with a culture of ownership and pragmatism.
Lead the design and operation of production machine learning systems for batch and online use cases with a focus on reliability and scalability.
Build and improve ML lifecycle infrastructure including training pipelines, inference workflows, monitoring, and automation.
Partner with cross-functional teams to translate business problems into ML solutions and guide prototypes to robust production systems.
Included Health is a healthcare company delivering integrated virtual care and navigation, aiming to raise the standard of healthcare for everyone. They are a remote-first organization offering comprehensive benefits and fostering a culture of inclusion.
Design and maintain ML model productionization infrastructure for high-visibility product features.
Collaborate with data science to streamline model training, validation, and deployment.
Implement robust monitoring and alerting for model performance, drift, and data quality.
The Athletic is a sports media company powered by one of the largest global newsrooms in sports, delivering in-depth coverage of professional and college teams across North America and Europe. With over 500 full-time staff, they foster a collaborative culture focused on high-quality journalism and data-driven innovation.
Design, develop, and deploy autonomous and multi-agent AI systems for reasoning, planning, and human-in-the-loop collaboration.
Engineer enterprise RAG pipelines with embeddings, hybrid retrieval, and prompt orchestration for explainable responses.
Build scalable backend services and APIs for enterprise AI workloads with security, reliability, and observability.
LTS builds an AI-native engineering platform to modernize legacy software systems, particularly for healthcare serving millions of Veterans. The engineering team is intentionally small, with every engineer having meaningful ownership and significant technical influence.
Own end-to-end delivery quality for major engagements, translating ambiguous client needs into practical execution plans.
Lead solution architecture and technical decision-making, making pragmatic tradeoffs between speed, quality, and client value.
Build and ship production AI/ML systems using Python, ML frameworks, and cloud-native infrastructure while mentoring other engineers.
Eliza is a technology services company and Advanced-tier OpenAI partner that helps organizations build and deploy AI solutions, from generative AI to predictive analytics. They are a collaborative, mission-driven team focused on real-world AI impact.
Design and implement AI capabilities for intelligent data characterization and decision support.
Evaluate, optimize, and deploy open-weight foundation models for resource-constrained edge environments.
Develop efficient inference pipelines and implement RAG, semantic search, and model optimization techniques.
Expression provides data fusion, analytics, AI/ML, software engineering, and spectrum management solutions to the U.S. Department of Defense and national security community. Founded in 1997 and headquartered in Washington DC, the company was ranked #1 on Washington Technology's 2018 Fast 50 and is a Top 20 Big Data Solutions Provider, fostering a collaborative culture with opportunities for growth.
Independently own high-value optimization initiatives across training, inference, or launch-readiness for important Ads ML workloads.
Diagnose bottlenecks in real production systems using profiling, benchmarking, and observability.
Build performance tooling, optimization playbooks, and efficiency primitives that benefit multiple teams.
Reddit is a community of communities built on shared interests and authentic conversations. With 100,000+ active communities and approximately 126 million daily active unique visitors, Reddit has a flexible workforce and values collaboration.
Design and build systems that generate synthetic environments for agent training and evaluation.
Build and maintain synthesis models for realistic replacement values at scale.
Build evaluation infrastructure that grades agent outcomes and discriminates between frontier models.
Tonic builds the data infrastructure behind modern AI, generating synthetic environments for agent training and de-identifying enterprise data. Eight years in, the company works with frontier AI labs and hundreds of enterprises, with a culture focused on solving hard data problems and shipping.
Design, build, and own agentic systems that produce client-ready financial deliverables from data ingestion to polished output.
Build evaluation and quality systems for generated deliverables, including deterministic checks and model-judged review.
Turn proprietary data into evidence-backed insight by building pipelines that discover and verify patterns.
Farsight is the agentic AI platform for financial services, helping investment banks and private equity firms automate nuanced workflows. The team comes from leading financial institutions and tech companies, focusing on hiring the best to become the best.
Lead a team to build, scale, and optimize the ML infrastructure powering drug discovery.
Collaborate with ML engineering, data science, and research teams to deliver scalable solutions.
Mentor and coach team members in MLOps, distributed computing, and infrastructure engineering.
Recursion is a clinical-stage TechBio company decoding biology to develop medicines. With a focus on AI and machine learning, the company fosters a culture of bold integrity and cross-functional collaboration.
Train, evaluate, and iterate on ML models for customer feedback, including custom fine-tuning pipelines.
Build and maintain LLM-powered features like retrieval pipelines and insight agents.
Design and run robust evaluation frameworks to measure model performance.
Chattermill helps large brands like Uber, Amazon, and Wise put customers at the center using AI. They offer a flexible, trust-based culture with a choice-first environment.
Evaluate LLM architecture logic for technical accuracy and audit ML code and notebooks for efficiency.
Refine RLHF frameworks to align models with human intent and analyze model reasoning in complex chain-of-thought prompts.
Benchmark performance by conducting comparative testing between model outputs based on technical metrics.
Prolific connects researchers with a global pool of participants for collecting high-quality human data to train AI models. With over 35,000 users, they focus on ethical data gathering to advance AI capabilities.
Spend your first weeks in the operator's seat, learning the customer's job from the inside before writing any code.
Ship production GenAI/LLM systems that move business unit metrics, not just complete scope.
Work embedded in small, senior teams alongside Principal Architects, owning the outcome from start to finish.
Provectus is a Premier AWS partner and an Anthropic Strategic Partner at the forefront of applied AI, helping enterprises turn Claude, agentic systems, and their own data into measurable business outcomes. With offices in North America, LATAM, and EMEA, we partner with clients worldwide and our team holds 100+ AWS certifications and is Claude Code certified.
Work directly with customers to understand their workflows and operational constraints.
Build and deploy AI-enabled applications, agents, and workflow automation using LLM techniques.
Own delivery from prototype to production, including architecture, backend services, and integrations.
Trase Systems provides an end-to-end platform for deploying and optimizing AI in the enterprise, focusing on bridging the 'last mile' of AI adoption. As a startup founded in 2023, the team is small, agile, and collaborative, with a strong emphasis on innovation and direct customer impact.
Design, develop, and deploy ML models, including large language models, for various NLP tasks.
Collaborate with cross-functional teams to gather requirements, define architectures, and iterate on model development.
Stay up-to-date with latest research and contribute to best practices for responsible ML development.
Reddit is a community of communities built on shared interests, passion, and trust, hosting the most open and authentic conversations on the internet. With over 100,000 active communities and approximately 126 million daily active users, it is one of the internet's largest sources of information, fostering a culture of authenticity and community.