Machine Learning Engineer

We’re looking for an experienced AI/ML Engineer to design, build, and deploy production-ready AI and machine learning solutions. This role is highly hands-on and focused on taking AI capabilities from concept through production, including generative AI, LLM-powered applications, intelligent automation, and traditional machine learning.

The ideal candidate combines strong software engineering fundamentals with practical experience building AI systems that solve real business problems.

What You’ll Do

• Design, build, test, and deploy production-grade AI/ML applications and services


• Develop applications using large language models (LLMs), generative AI, and modern ML techniques


• Build RAG pipelines, AI agents, workflow automation, and intelligent search/retrieval solutions


• Integrate commercial and open-source models into enterprise applications


• Develop and optimize prompts, context management, embeddings, vector search, and model orchestration


• Build APIs and backend services that expose AI/ML capabilities to applications and internal systems


• Evaluate model and application performance for accuracy, reliability, latency, and cost


• Design data pipelines supporting model training, inference, retrieval, and evaluation


• Implement appropriate guardrails, monitoring, observability, and security controls for production AI


• Work closely with engineering, product, data, and business stakeholders to identify high-value AI use cases


• Prototype quickly while maintaining a clear path from proof of concept to scalable production systems


• Stay current with rapidly evolving AI models, frameworks, architectures, and development practices

What We’re Looking For

• 5+ years of professional software engineering, machine learning engineering, or related experience


• Strong programming skills in Python


• Hands-on experience building and deploying AI/ML systems in production


• Experience working with LLMs and APIs from providers such as OpenAI, Anthropic, Google, or comparable open-source models


• Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation


• Strong understanding of APIs, microservices, distributed systems, and modern application architecture


• Experience with ML/AI frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar technologies


• Experience deploying AI/ML workloads in AWS, Azure, or GCP


• Familiarity with Docker, CI/CD, Git, and modern DevOps/MLOps practices


• Experience working with structured and unstructured data


• Strong problem-solving skills and the ability to translate ambiguous business problems into practical technical solutions

Nice to Have

• Experience building agentic AI systems and multi-step AI