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 DoDesign, build, test, and deploy production-grade AI/ML applications and servicesDevelop applications using large language models (LLMs), generative AI, and modern ML techniquesBuild RAG pipelines, AI agents, workflow automation, and intelligent search/retrieval solutionsIntegrate commercial and open-source models into enterprise applicationsDevelop and optimize prompts, context management, embeddings, vector search, and model orchestrationBuild APIs and backend services that expose AI/ML capabilities to applications and internal systemsEvaluate model and application performance for accuracy, reliability, latency, and costDesign data pipelines supporting model training, inference, retrieval, and evaluationImplement appropriate guardrails, monitoring, observability, and security controls for production AIWork closely with engineering, product, data, and business stakeholders to identify high-value AI use casesPrototype quickly while maintaining a clear path from proof of concept to scalable production systemsStay current with rapidly evolving AI models, frameworks, architectures, and development practicesWhat We’re Looking For5+ years of professional software engineering, machine learning engineering, or related experienceStrong programming skills in PythonHands-on experience building and deploying AI/ML systems in productionExperience working with LLMs and APIs from providers such as OpenAI, Anthropic, Google, or comparable open-source modelsExperience with RAG, embeddings, vector databases, prompt engineering, and LLM evaluationStrong understanding of APIs, microservices, distributed systems, and modern application architectureExperience with ML/AI frameworks such as PyTorch, TensorFlow, Hugging Face, LangChain, LlamaIndex, or similar technologiesExperience deploying AI/ML workloads in AWS, Azure, or GCPFamiliarity with Docker, CI/CD, Git, and modern DevOps/MLOps practicesExperience working with structured and unstructured dataStrong problem-solving skills and the ability to translate ambiguous business problems into practical technical solutionsNice to HaveExperience building agentic AI systems and multi-step AI