Design, build, and deploy production machine learning and LLM systems, including RAG pipelines, agentic workflows, fine-tuning, and embeddings. Own technical delivery from architecture through monitoring and iteration, collaborate with client engineering and product teams, mentor junior ML engineers, and help establish internal technical standards and best practices.
About TensorOps
TensorOps is a boutique AI consultancy that bridges strategy and execution, we design and ship production-grade AI systems for enterprise clients, from Fortune 500 companies to fast-growing unicorns. Our work spans agentic AI, LLM fine-tuning, RAG systems, and ML-driven products, deployed on AWS, GCP, and Azure.
We've shipped AI systems impacting 200M+ end users daily, partnered with 11 unicorns and NASDAQ-listed companies (including Notion, ServiceNow, JFrog, Seeking Alpha, Armis, and GoCardless), and get 95% of validated ideas into production within two months. We're Google Cloud, AWS, and Cloudflare partners, and we're 100% remote by design.
About the roleWe're hiring a Mid/Senior ML Engineer to contribute to technical direction across client engagements and mentor a growing team of junior ML engineers. You'll work directly with clients, taking AI systems from prototype to production-grade deployment.
In this role, you will:
- 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
- Work directly with client engineering and product teams to translate business needs into scoped, shippable technical solutions
- Mentor and support other ML engineers on the team — code reviews, technical guidance, and knowledge sharing
- Help shape internal best practices, tooling, and technical standards as the team grows
- Represent TensorOps technically in client conversations, workshops, and (optionally) at industry conferences
You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning.
Requirements- 2+ years of professional experience in Machine Learning, AI Engineering, or a related role (Mid-level) / 5+ years for Senior
- Strong hands-on skills in Python, writing clean, efficient, well-documented, production-quality code
- Proven experience designing, training, optimizing, and deploying ML models independently (e.g., PyTorch, TensorFlow, Scikit-learn)
- Experience building GenAI & LLM systems: RAG pipelines, chatbot architectures, and applications using tools like LangChain
- Familiarity with MLOps & production ML practices: model versioning, monitoring, CI/CD for ML workflows
- Experience deploying and scaling ML systems on AWS, GCP, or Azure
- Strong performance optimization and debugging skills (diagnosing complex issues and improving system reliability and efficiency)
- Experience working with stakeholders or clients is a plus
- 100% Remote Work: no mandatory office days, work from wherever
- Funded certifications: fully paid AWS and GCP professional certifications
- Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
- International Clients: Collaborate with global organizations and solve real-world challenges at scale
- Urban Sports Club Membership: Supporting your physical and mental wellbeing
- Monthly Bolt Credits: For rides
- Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate
Similar Jobs
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Operate and maintain Insitu unmanned aircraft systems, conduct preflight planning and mission briefings, collect and analyze flight data, perform troubleshooting and field maintenance, coordinate with customers and subject-matter experts, manage spares inventory, and deploy worldwide in austere environments to support customer missions.
Top Skills:
Basic NetworkingIntegratorRq21ScaneagleUas Platforms
Aerospace • Information Technology • Software • Cybersecurity • Design • Defense • Manufacturing
Support export compliance for unmanned aerial systems: draft, submit, and manage ITAR/EAR licenses and commodity jurisdiction requests; classify technical data; manage license lifecycle and documentation; coordinate with stakeholders and provide licensing guidance as an empowered official.
Top Skills:
ExcelMicrosoft TeamsOcr EaseSharepoint
Cloud • Computer Vision • Information Technology • Sales • Security • Cybersecurity
Leads enterprise security software sales across assigned Florida accounts, focusing on prospecting, qualification, new customer acquisition, revenue delivery, forecasting, and closing complex enterprise deals. Develops account plans, engages executive decision-makers, coordinates onboarding and adoption with internal teams, manages CRM activity, collaborates with partners and marketing, and provides customer feedback. Requires deep expertise in security software sales, consultative selling, negotiation, business value, and AI-enabled workflows.
Top Skills:
Artificial IntelligenceCrm SoftwareCybersecurityEnterprise Security SoftwareFalcon FlexMarketing Software
What you need to know about the Boston Tech Scene
Boston is a powerhouse for technology innovation thanks to world-class research universities like MIT and Harvard and a robust pipeline of venture capital investment. Host to the first telephone call and one of the first general-purpose computers ever put into use, Boston is now a hub for biotechnology, robotics and artificial intelligence — though it’s also home to several B2B software giants. So it’s no surprise that the city consistently ranks among the greatest startup ecosystems in the world.
Key Facts About Boston Tech
- Number of Tech Workers: 269,000; 9.4% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Thermo Fisher Scientific, Toast, Klaviyo, HubSpot, DraftKings
- Key Industries: Artificial intelligence, biotechnology, robotics, software, aerospace
- Funding Landscape: $15.7 billion in venture capital funding in 2024 (Pitchbook)
- Notable Investors: Summit Partners, Volition Capital, Bain Capital Ventures, MassVentures, Highland Capital Partners
- Research Centers and Universities: MIT, Harvard University, Boston College, Tufts University, Boston University, Northeastern University, Smithsonian Astrophysical Observatory, National Bureau of Economic Research, Broad Institute, Lowell Center for Space Science & Technology, National Emerging Infectious Diseases Laboratories
