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.

Increase your chances of an interview by reading the following overview of this role before making an application.

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 xhyhwjd 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