Machine Learning Engineer

3 weeks ago

Kolkatta, India RPSG Ventures Full time

Introduction – RP-SG Group :

Legacy is about building the future by honoring the past. With a rich heritage, RPSG Group today stands as one of the most esteemed and fastest-growing conglomerates in India. The Group inspires trust and credibility through its value-driven business culture and thought leadership. The Group's businesses include power and energy, performance and specialty chemicals, retail, IT-enabled services, FMCG, media and entertainment, plantations, and sports.

The RPSG Group stands as one of India’s new-age and fastest-growing conglomerates, with a turnover of approximately US$4.5 billion and an asset base exceeding US$6 billion. Driven by a dedicated workforce of over 50,000 employees from diverse backgrounds, the Group has a presence in 50+ countries.

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Job Summary :

We are looking for a skilled AI/ML Engineer to design, develop, and deploy AI/GenAI models and solutions. The role requires a blend of strong programming expertise, algorithmic problem-solving skills, and a passion for innovation.

Responsibilities :

  • Design, build, and train AI/ML models, including LLMs, transformers, and generative systems.
  • Collaborate with data scientists to implement scalable AI/ML pipelines.
  • Optimize model performance for deployment in production environments.
  • Research and implement state-of-the-art AI/ML techniques to solve business challenges.
  • Develop APIs and interfaces for integrating AI models with existing systems.
  • Monitor and maintain deployed AI models to ensure reliability and scalability.
  • Ensure compliance with AI ethics and organizational data privacy policies.

Qualifications :

  • Engineering degree (BE/BTech) or MSc in Computer Science, Physics, or a related scientific field with a strong mathematical foundation.
  • 4–7 years of experience in Data & Analytics, with hands-on experience in AI/GenAI model development and deployment.
  • Proficiency in Python and frameworks like TensorFlow, PyTorch, and Scikit-learn.
  • Hands-on experience with ML Ops tools such as MLflow, Kubeflow, or SageMaker for model lifecycle management.
  • Familiarity with containerization and orchestration tools such as Docker and Kubernetes for deploying AI models.
  • Experience with version control systems like Git and CI/CD pipelines for continuous integration and deployment.
  • Strong understanding of NLP, computer vision, or reinforcement learning techniques.
  • Experience with cloud platforms such as AWS, Azure, or Google Cloud.
  • Excellent problem-solving and teamwork skills.

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