Machine Learning Engineer

The Lead AI/ML Engineer will act as the technical authority within the AI practice, combining hands-on development with technical leadership. This role involves designing scalable AI architectures, leading engineering teams, and delivering complex, client-facing solutions in production environments—primarily on AWS.

Technical Leadership

• Define end-to-end AI/ML solution architectures aligned with business goals

• Drive decisions on models, frameworks, infrastructure, and design patterns

• Establish engineering best practices (code quality, testing, documentation, MLOps)

• Mentor engineers and support technical growth

• Translate business requirements into technical solutions with stakeholders

• Support pre-sales activities (estimation, proposals, client presentations)

Development & Implementation

• Build and deploy ML pipelines (supervised, unsupervised, reinforcement learning)

• Develop GenAI solutions using LLMs (RAG, agents, multi-agent systems)

• Implement fine-tuning techniques (LoRA, RLHF, instruction tuning)

• Design data ingestion, preprocessing, and embedding pipelines

• Define evaluation, monitoring, and observability strategies

Infrastructure & MLOps

• Design and manage AWS-based ML infrastructure (training to monitoring)

• Implement CI/CD pipelines for ML workflows

• Ensure model reproducibility (data/model versioning)

• Define governance policies (data lineage, compliance, access control)

Requirements

Experience

• 6+ years in AI/ML in production environments

• 2+ years in technical leadership or architecture roles

• Consulting experience is a plus

AI/ML & Data

• Strong knowledge of ML algorithms and deep learning (PyTorch/TensorFlow)

• Experience with feature engineering, model tuning, and evaluation

• Familiarity with time series, forecasting, and anomaly detection

Generative AI / LLMs

• Hands-on experience with LLMs (OpenAI, Claude, Llama, etc.)

• Experience with frameworks like LangChain, LlamaIndex, or similar

• Strong knowledge of RAG architectures and prompt engineering

• Experience with multi-agent systems and fine-tuning techniques

Cloud & Infrastructure

• Advanced AWS experience (SageMaker, Bedrock, Lambda, ECS/EKS, S3, etc.)

• Knowledge of Azure AI (nice to have)

• Experience with Docker, Kubernetes, Terraform or AWS CDK

• Familiarity with vector databases (Pinecone, Weaviate, etc.)

MLOps & Engineering

• Advanced Python and strong software engineering practices

• Experience with MLflow, DVC, or similar tools

• Knowledge of data pipelines (Airflow, Spark, Glue)

• Experience with SQL and NoSQL databases

Additional Skills

• Fluent English (C1/C2)

• Strong communication with technical and non-technical stakeholders

• Experience with project planning and estimations

Education

• Degree in Computer Science, Engineering, Mathematics, or related fields

• Relevant certifications are a plus (AWS, ML Specialty, etc.)