Machine Learning Engineer / Lead (contractual)

Engagement Type:

Location:

About the Role

experienced Machine Learning Engineers

You'll work on designing, developing, and deploying scalable ML solutions across domains driving innovation, automation, and data-driven decision-making.

Key Responsibilities

• Design, develop, and implement end-to-end

  ML pipelines

  including data ingestion, feature engineering, and model deployment.
• Collaborate with business, data, and product teams to deliver actionable insights and AI-driven solutions.
• Build scalable data pipelines using

  PySpark

  and integrate ML models into production environments.
• Develop and fine-tune models for

  forecasting, NLP, image/video analytics

  , and other advanced ML use cases.
• Perform

  exploratory data analysis

  , model performance evaluation, and hyperparameter tuning.
• Implement

  MLOps best practices

  for model lifecycle management, versioning, monitoring, and CI/CD automation.
• Leverage

  AWS services

  such as Sagemaker, Bedrock, and Kendra for model training and deployment.
• Encourage a culture of continuous learning, experimentation, and innovation within the team.
  

Required Skills & Experience

• Strong programming expertise in

  Python

  .
• 310 years of hands-on experience in

  data/feature pipelines

  using

  PySpark

  .
• Proficiency in

  ML model lifecycle

  , from data prep to production deployment.
• Strong foundation in

  statistics and probability

  (hypothesis testing, distributions, regression, etc.).
• Working knowledge of

  MLOps tools and frameworks

  for scalable deployments.
• Exposure to

  AWS Cloud

  (Sagemaker, Bedrock, Kendra) and related services.
• Familiarity with

  technical architecture

  ,

  model management

  , and

  operational best practices

  .

Good to Have

• Experience with

  Generative AI and LLMs

  (LangChain, LlamaIndex, Foundation Model Tuning, Data Augmentation).
• Experience with

  Docker and Kubernetes

  for containerized deployments.
• Hands-on exposure to

  time-series modeling, forecasting, and advanced analytics

  .

Who Should Apply

• Professionals passionate about solving complex problems using AI/ML.
• Engineers available for

  immediate or near-term joining

  .
• Candidates open to

  contractual/consulting engagements

  with leading enterprise clients.