Mid/Senior AI Engineer

Posted 7 Hours Ago
Hiring Remotely in USA
Remote
Senior level
Artificial Intelligence • Machine Learning • Professional Services • Business Intelligence • Big Data Analytics
Your Partners in AI
The Role
Design, build, and deploy production-grade ML and LLM systems (RAG, fine-tuning, embeddings, agentic workflows). Own end-to-end technical delivery, collaborate with client teams, mentor junior engineers, improve MLOps/CI/CD, and shape internal best practices and tooling for scalable AI products.
Summary Generated by Built In
 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 role

We'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
What We Offer
  • 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

Skills Required

  • 2+ years professional ML/AI experience for Mid-level; 5+ years for Senior
  • Strong hands-on skills in Python and production-quality code
  • Proven experience designing, training, optimizing, and deploying ML models (PyTorch, TensorFlow, Scikit-learn)
  • Experience building GenAI & LLM systems, including RAG pipelines, chatbot architectures, and LangChain
  • Familiarity with MLOps and 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
  • Experience working with stakeholders or clients
Am I A Good Fit?
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The Company
HQ: New York, New York
17 Employees
Year Founded: 2022

What We Do

TensorOps is a global AI, ML & Data consulting and professional services firm that accelerates business value through rapid, efficient technology adoption, combining strategic executive consultancy with hands-on deployment to deliver tailored solutions across adtech, healthcare, fintech and beyond. With a multidisciplinary team of 20 engineers and business strategists, spanning through Portugal, USA, UK and Israel, we ensure the right AI approach for every organisation, from first-time adopters to established industry leaders, such as Notion, KLA, Minute Media, and Seeking Alpha. TensorOps is a Google Cloud Partner and AWS Partner

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