AI Machine Learning Engineer

2 days ago

Noida, Uttar Pradesh, India beBeeData Full time ₹ 1,50,00,000 - ₹ 2,00,00,000

About our organization: With over two decades of experience building innovative digital products and solutions, we deliver impactful results to our clients. We have been a pioneer in driving digital innovation and tech-enabled transformation across a wide range of industries.

Job Title

Data Science Specialist

Experience: 15-20 years

Location: Noida

Work mode: Hybrid (3 days WFO)

We are looking for an experienced Senior Lead Data Scientist/ML Engineer with a strong blend of pre-sales expertise, team leadership, and technical proficiency across classical machine learning, deep learning, and generative AI.

Key Responsibilities:

  • Collaborate with the sales and business development teams to identify client needs and formulate AI/ML solutions.
  • Present technical concepts, project proposals, and proof-of-concepts (POCs) to prospects and clients.
  • Translate complex client requirements into actionable project scopes, estimates, and technical proposals.
  • Provide direction, mentorship, and performance feedback to a team of data scientists and ML engineers.
  • Establish best practices in solution design, code reviews, model validation, and production deployment.
  • Drive the strategic roadmap for AI initiatives, ensuring alignment with organizational goals and market trends.
  • Apply classical machine learning techniques (e.g., regression, clustering, decision trees, ensemble methods) to solve diverse business problems.
  • Design and optimize data pipelines, feature engineering processes, and model selection strategies.
  • Ensure robust model evaluation, tuning, and performance monitoring in production environments.
  • Develop and maintain deep learning models using frameworks such as TensorFlow or PyTorch for tasks like computer vision, NLP, or recommendation systems.
  • Explore and build solutions leveraging generative AI (GANs, VAEs, or transformer-based architectures) for innovative product features and services.
  • Champion research and experimentation with state-of-the-art AI models, staying ahead of industry advances.

Project Delivery & MLOps

  • Lead end-to-end ML project lifecycles, from data exploration and model development to deployment and post-launch maintenance.
  • Implement MLOps best practices (CI/CD, containerization, model versioning) on cloud or on-premise infrastructures.
  • Collaborate with DevOps and engineering teams to integrate ML solutions seamlessly into existing systems.

Stakeholder Management & Communication

  • Serve as a key technical advisor to executive leadership, product managers, and client teams.
  • Communicate complex AI/ML findings in clear, actionable terms to both technical and non-technical audiences.
  • Advocate data-driven decision-making and foster a culture of innovation within the organization.

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