Mid/Senior AI Engineer
T
TensorOpsAI Consultancy
100% Remote Work: no mandatory office days, work from whereverFull-TimeSenior
Salary not disclosed
Apply NowOpens the employer's application page
Job Details
- Experience
- 2+ years for Mid-level / 5+ years for Senior
- Required Skills
- AWSPythonPyTorchTensorflowscikit-learnLLMMLOpsGenerative AILangChain
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
Responsibilities
- 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
View Full Description & ApplyYou'll be redirected to the employer's site
