ML Engineer

2 days ago

Gurgaon, Haryana, India Weekday AI Full time ₹ 12,00,000 - ₹ 36,00,000 per year

This role is for one of the Weekday's clients

Min Experience: 6 years

Location: Gurugram

JobType: full-time

We are looking for an experienced Machine Learning Engineer with 6–12 years of hands-on expertise in designing, developing, and deploying AI/ML solutions at scale. The ideal candidate is strong in end-to-end model development, has a deep understanding of applied machine learning, and can translate complex business problems into production-ready ML systems. This role requires a blend of technical excellence, problem-solving capability, data engineering awareness, and a strong understanding of modern AI/ML workflows.

Requirements
Key Responsibilities

1. End-to-End ML Model Development

  • Design, build, and optimize machine learning models for classification, regression, recommendation, NLP, or other AI applications.
  • Conduct exploratory data analysis, data preprocessing, feature engineering, and model selection.
  • Implement ML algorithms using frameworks such as TensorFlow, PyTorch, Scikit-learn, or similar.
  • Continuously evaluate model performance using appropriate metrics and ensure model drift monitoring and retraining.

2. AI/ML Solution Architecture & Deployment

  • Architect scalable ML pipelines using tools like MLflow, Kubeflow, Airflow, or Azure ML/ SageMaker pipelines.
  • Deploy models to production using containerization and cloud-native services (AWS, Azure, GCP).
  • Collaborate with engineering teams to integrate ML models into production systems with APIs, microservices, or streaming data solutions.

3. Data Engineering & Pipeline Optimization

  • Work closely with data engineering teams to define data requirements, ensure data quality, and build robust feature pipelines.
  • Optimize model training and inference pipelines for speed, cost efficiency, and reliability.
  • Leverage distributed computing frameworks (Spark, Ray, or Dask) for large-scale ML training.

4. Research & Innovation in AI/ML

  • Stay updated with advancements in AI/ML, including transformers, LLMs, deep learning architectures, and generative AI.
  • Experiment with cutting-edge models and techniques to improve accuracy, performance, or automation of ML workflows.
  • Drive proof-of-concept development and feasibility studies for new AI-driven initiatives.

5. Cross-Functional Collaboration

  • Partner with product managers, data scientists, analysts, and engineering teams to define and execute ML roadmaps.
  • Translate business requirements into technical specifications and deliver scalable ML solutions.
  • Communicate model insights, predictions, and performance results to both technical and non-technical stakeholders.
Qualifications & Experience
  • 6–12 years of hands-on industry experience as an ML Engineer, Applied ML Engineer, or AI Engineer.
  • Strong programming expertise in Python and ML libraries such as TensorFlow, PyTorch, Scikit-learn, and ecosystem tools like NumPy and Pandas.
  • Deep understanding of ML algorithm fundamentals, statistical modeling, deep learning, NLP, and optimization techniques.
  • Experience working with cloud platforms (AWS, Azure, or GCP) and containerization tools (Docker, Kubernetes).
  • Proficiency in building and maintaining ML pipelines, CI/CD workflows, and model monitoring systems.
  • Strong understanding of data structures, algorithms, and software engineering best practices.
  • Experience with distributed computing, GPU acceleration, or handling large-scale datasets is a plus.
  • Excellent problem-solving, analytical thinking, and communication skills.

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