Machine Learning Engineer

Job Description

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

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• Design, build, test, and deploy production-grade AI/ML applications and services
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• Develop applications using large language models (LLMs) , generative AI, and modern ML techniques
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• Build RAG pipelines , AI agents, workflow automation, and intelligent search/retrieval solutions
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• Integrate commercial and open-source models into enterprise applications
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• Develop and optimize prompts, context management, embeddings, vector search, and model orchestration
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• Build APIs and backend services that expose AI/ML capabilities to applications and internal systems
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• Evaluate model and application performance for accuracy, reliability, latency, and cost
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• Design data pipelines supporting model training, inference, retrieval, and evaluation
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• Implement appropriate guardrails, monitoring, observability, and security controls for production AI
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• Work closely with engineering, product, data, and business stakeholders to identify high-value AI use cases
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• Prototype quickly while maintaining a clear path from proof of concept to scalable production systems
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• Stay current with rapidly evolving AI models, frameworks, architectures, and development practices
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What We’re Looking For

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• 5+ years of professional software engineering, machine learning engineering, or related experience
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• Strong programming skills in Python
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• Hands-on experience building and deploying AI/ML systems in production
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• Experience working with LLMs and APIs from providers such as OpenAI, Anthropic, Google, or comparable open-source models
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• Experience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluation
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• Strong understanding of APIs, microservices, distributed systems, and modern application architecture
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• Experience with ML/AI frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex , or similar technologies
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• Experience deploying AI/ML workloads in AWS, Azure, or GCP
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• Familiarity with Docker, CI/CD, Git, and modern DevOps/MLOps practices
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• Experience working with structured and unstructured data
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• Strong problem-solving skills and the ability to translate ambiguous business problems into practical technical solutions
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Nice to Have

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• Experience building agentic AI systems and multi-step AI
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