Senior AI Engineer

Posted 3 Days 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, deploy, monitor, and optimize production machine learning and LLM systems, including RAG pipelines, agentic workflows, fine-tuned models, and embeddings. The role owns technical delivery from architecture through iteration, collaborates with enterprise clients, mentors junior ML engineers, conducts code reviews, and helps establish internal engineering standards and tooling.
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 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
  • 5+ years of professional experience in Machine Learning, AI Engineering, or a related role
  • 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

  • 5+ years of professional experience in Machine Learning, AI Engineering, or a related role
  • Strong hands-on Python skills, including clean, efficient, documented production-quality code
  • Experience designing, training, optimizing, and independently deploying machine learning models
  • Experience with PyTorch, TensorFlow, or Scikit-learn
  • Experience building generative AI and LLM systems, including RAG pipelines and chatbot architectures
  • Experience using tools such as LangChain
  • Familiarity with MLOps and production ML practices, including model versioning, monitoring, and CI/CD for ML workflows
  • Experience deploying and scaling machine learning 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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