AI ML Engineer

We're seeking an
AI/ML Engineer
to design, build, and deploy intelligent systems that leverage large language models, machine learning, and agentic AI architectures. You'll work at the intersection of ML research and production engineering—transforming cutting-edge AI capabilities into robust, scalable solutions that drive real business impact.

This is a hands-on role where you'll architect AI systems from the ground up, experiment with novel approaches, and ship production-grade ML applications. You'll collaborate with engineering, product, and data teams to push the boundaries of what's possible with AI.

What You'll Do

AI System Development

• Design and build
  production AI/ML systems
  including agentic workflows, multi-model pipelines, and intelligent automation
• Develop and optimize
  LLM-based applications
  using prompt engineering, RAG (Retrieval-Augmented Generation), and fine-tuning techniques
• Build
  AI agent frameworks
  that orchestrate complex reasoning, tool use, and multi-step workflows

ML Engineering & Operations

• Train, evaluate, and deploy
  machine learning models
  across classification, NLP, recommendation, and generative tasks
• Implement
  MLOps pipelines
  for model versioning, monitoring, A/B testing, and continuous improvement
• Optimize model performance, latency, and cost for production environments

Data & Infrastructure

• Design
  vector databases, embedding systems, and semantic search
  architectures for AI applications
• Build scalable
  data pipelines
  for model training, inference, and continuous learning
• Create
  evaluation frameworks
  to measure AI system quality, safety, and performance

Collaboration & Innovation

• Partner with cross-functional teams to identify high-impact AI use cases and translate requirements into technical solutions
• Stay current with AI research and rapidly prototype emerging techniques (new model architectures, agent frameworks, tools)
• Contribute to architectural decisions, code reviews, and engineering best practices

Required Qualifications

Technical Foundation

• Bachelor's or master's degree in computer science
  , Machine Learning, Mathematics, Statistics, or related field (or equivalent practical experience)
• 5+ years
  of software engineering experience with
  3+ years specifically in AI/ML development
• Strong programming skills in
  Python
  and ML frameworks (
  PyTorch, TensorFlow, or JAX
  )

AI/ML Expertise

• Hands-on experience building applications with
  LLMs
  (GPT, Claude, Llama, etc.) and understanding of their capabilities/limitations
• Proficiency with
  AI frameworks and tools
  : LangChain, LlamaIndex, DSPy, Hugging Face, OpenAI API, Anthropic API
• Experience with
  machine learning techniques
  : supervised/unsupervised learning, NLP
• Understanding of
  prompt engineering, RAG architectures, and context optimization
  for LLM systems

Software Engineering

• Strong fundamentals in
  data structures, algorithms, and system design
• Experience building
  APIs, microservices, and distributed systems
  using modern frameworks (Fast API, , etc.)
• Proficient with
  cloud platforms
  (AWS, GCP, or Azure) and containerization (Docker, Kubernetes)
• Familiarity with
  vector databases
  (Pinecone, Weaviate, ChromaDB, Qdrant) and SQL/NoSQL databases

Preferred Qualifications

• Experience with
  model fine-tuning, RLHF, or custom model training
• Knowledge of
  AI safety, alignment, and evaluation methodologies
• Contributions to
  open-source AI/ML projects
  or research publications
• Familiarity with
  AI agent architectures
  : ReAct, Chain-of-Thought, tool use, multi-agent systems
• Experience with
  frontend frameworks
  (React, ) for building AI-powered interfaces
• Background in
  MLOps tools
  : Weights & Biases, MLflow, Kubeflow, or similar platforms

What We're Looking For

Experimenters & Builders
— You love trying new models, techniques, and architectures. You're equally comfortable reading research papers and writing production code.

Systems Thinkers
— You understand how to design end-to-end AI systems that balance accuracy, latency, cost, and user experience.

Fast Learners
— The AI landscape evolves weekly. You're excited by rapid change and can quickly evaluate and adopt new tools and approaches.

Pragmatic Problem-Solvers
— You choose the right tool for the job—whether that's a state-of-the-art model, a simple heuristic, or something in between.

Collaborative Innovators
— You communicate complex technical concepts clearly, mentor others, and thrive in cross-functional environments.

Tools & Technologies We Use

• LLM Platforms
  : OpenAI, Anthropic, open-source models (Llama, Mistral)
• Frameworks
  : LangChain, LlamaIndex, Hugging Face Transformers
• ML Stack
  : PyTorch, scikit-learn, pandas, numpy
• Vector DBs
  : Pinecone, Weaviate, ChromaDB
• Cloud
  : AWS (SageMaker, Bedrock) / GCP (Vertex AI) / Azure (OpenAI Service)
• Development
  : Python, TypeScript, React, , FastAPI
• MLOps
  : Docker, Kubernetes, GitHub Actions, Weights & Biases
• AI Dev Tools
  : Cursor, GitHub Copilot, Claude for coding

Why Join Us?

• Work on
  cutting-edge AI systems
  that directly impact users and business outcomes
• Access to
  latest AI models and tools
  with budget for experimentation
• Collaborate with talented engineers, data scientists, and researchers
• Rapid iteration
  culture—ship fast, learn, and improve
• Opportunities to
  shape AI strategy
  and technical direction

We're building AI systems that matter. If you're passionate about pushing the boundaries of what's possible with machine learning and want to see your work in production, we'd love to hear from you.