AI​/ML Hybrid

Position :
AI/ML Engineer

Location :
St. Louis Hybrid

Duration:
Full Time

• 3 years of hands-on experience in machine learning, data science, search relevance, or ranking systems.
• Proven expertise in Python and ML frameworks (MLFlow, Tensor Flow, PyTorch, Scikit-learn, or equivalent).
• Strong background in statistical analysis, data exploration, and working with large-scale datasets.
• Experience with feature engineering, data preprocessing, and data

• 10 years of software engineering experience, with deep recent time leading production AI/LLM systems
• Seasoned hands-on coder; still writes production Python regularly
• Seasoned system designer for AI systems at scale retrieval, agents, evaluation, latency, and cost, vector databases/pipelines
• Strong experience building and maintaining production-grade backend applications.
• Experience designing and developing RESTful APIs and distributed systems.
• Strong SQL skills and experience working with relational databases; familiarity with No
  
  SQL databases or modern data storage technologies is a plus.
• Solid understanding of data engineering fundamentals, including data quality, validation, transformation, modeling, and efficient storage.
• Experience designing systems that process large datasets reliably and efficiently.
• Experience with cloud platforms such as Google Cloud Platform (Google Cloud Platform) or AWS.
• Experience using Docker, Git, CI/CD pipelines, automated testing frameworks, and modern software engineering best practices.
• Core engineering stack
  • Languages:
    
    Python, REST API, Pandas, Num Py
  • Cloud and infrastructure: AWS Services and/or Google Cloud Platform, Kubernetes, Bedrock
  • Distributed systems: event-driven architectures, including Kafka
  • Orchestration Frameworks:
    Lang Graph, Lang Chain, Air Flow, etc.
  • Vector Databases like Qdrant

• Experience with Kubernetes and container orchestration.
• Familiarity with event-driven architectures and messaging platforms such as Kafka.
• Familiarity with ML model deployment and inference pipelines

• Lead technical strategy for AI/LLM systems across multiple products
• Architect retrieval, orchestration, agentic, and evaluation systems that run reliably in production
• Set the standards for AI safety, evaluation, observability, and responsible rollout in a regulated context
• Mentor Junior-level engineers into strong AI engineers;
  Employ AI Native development skills to multiply the productivity (Claude, etc.)
• Lead the frontier: evaluate new models, techniques, and tools, and bring the right ones into the team
• Design, develop, and maintain scalable Python applications and backend services.
• Build systems that ingest, validate, transform, and manage structured and unstructured data in production environments.
• Design data models and storage solutions that support scalable, high-performance applications.
• Develop reusable components for data processing, validation, enrichment, and feature generation

Thanks & Regards

Rakesh Vangala

Team Lead

Burgeon IT Services LLC.

Email

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