Principal Machine Learning Engineer

Principal Machine Learning Engineer



Location: Remote

Type: Contract-to-Hire

Experience: 6-12+ years

Education: Master's or PhD preferred


LLM/Generative AI, Multi-Agent AI (Planner/Executor, ReAct, Tool-Use), RAG, Embeddings, Retrieval Optimization, NLP, Transformers, Deep Learning, Model Fine-Tuning, PyTorch, Hugging Face, LangChain/LlamaIndex, Kubernetes, Vector Databases, ML Monitoring & Observability.



Core Stack: Python, PyTorch, Hugging Face, LangChain/LlamaIndex, RAG, LLMs, Transformers, Vector Databases, Kubernetes, Multi-Agent AI, ML Observability.


Job Summary


We are seeking 2 Principal Machine Learning Engineers to join a collaborative team building and deploying advanced AI and LLM-based solutions. The ideal candidate will have strong hands-on experience in Machine Learning, Generative AI, LLMs, RAG and multi-agent systems , with the ability to translate complex technical concepts into practical business solutions.


The role requires someone who has spent the last 2-3 years heavily focused on modern AI/LLM technologies and has experience taking ML systems from development through production.


Required Skills

• 6-12+ years of experience in Data Science and Machine Learning Engineering
• Strong hands-on experience building and deploying LLM-based systems
• Expertise in Generative AI and NLP
• Proven experience with multi-agent architectures , including Planner/Executor, Tool-Use Agents and ReAct-style agents
• Strong experience with Retrieval-Augmented Generation (RAG)
• Hands-on experience with embeddings and retrieval optimization
• Experience developing LLM/ML model evaluation frameworks
• Strong knowledge of Transformers and Deep Learning
• Experience with model fine-tuning
• Hands-on experience with PyTorch and Hugging Face
• Experience with LangChain and/or LlamaIndex
• Experience working with Kubernetes
• Experience with vector databases
• Experience designing and operating production-grade ML systems
• Experience with ML monitoring, observability and evaluation

Preferred Qualifications

• Master's or PhD in Computer Science, Machine Learning, Artificial Intelligence, Data Science or a related field
• Experience architecting enterprise-scale AI/LLM platforms
• Experience with production agentic AI systems
• Strong understanding of LLM evaluation, hallucination reduction and retrieval quality
• Experience with cloud-based ML/AI infrastructure
• Strong communication and stakeholder management skills

Key Responsibilities

• Design, develop and deploy production-grade LLM and Generative AI solutions
• Build and optimize RAG pipelines , embeddings and retrieval systems
• Design and implement multi-agent architectures
• Fine-tune and evaluate transformer-based models
• Develop scalable ML/AI services and infrastructure
• Build monitoring, observability and evaluation frameworks for production AI systems
• Collaborate with data scientists, engineers, product teams and business stakeholders
• Translate business requirements into scalable AI/ML solutions
• Provide technical leadership and mentorship across AI/ML initiatives