Data Science Manager

CommerceIQ; Bengaluru; On-site; INR 1,500,000 - 2,500,000; Full time

Job summary

A leading AI solutions provider in Bengaluru is seeking an experienced individual with a profound background in machine learning, deep learning, and NLP. Ideal candidates must have experience in training and fine-tuning models, along with strong leadership capabilities to guide a team of applied scientists. The role involves collaborative efforts across departments to create impactful AI solutions. A Master's or PhD in a relevant field and over 7 years in applied ML are necessary, with at least 2 years in a managerial role.

Qualifications

• 7+ years of hands-on experience in applied machine learning and data science.
• At least 2+ years in a leadership or managerial role.
• Basic understanding of MLOps best practices.

Responsibilities

• Lead and mentor a team of applied scientists and ML engineers.
• Design, evaluate, and improve models using robust validation strategies.
• Translate cutting-edge research into scalable solutions for business needs.

Skills

Machine learning

Deep learning

Natural Language Processing (NLP)

PyTorch

TensorFlow

Hands-on expertise with PEFT

Data pipelines management

Strong problem-solving

Education

Master's or Ph.D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field

Tools

Hugging Face ecosystem

Spark

Databricks

Job description

Strong background in machine learning, deep learning, and NLP, with proven experience in training and fine-tuning large-scale models (LLMs, transformers, diffusion models, etc.)

• Hands‑on expertise with Parameter‑Efficient Fine‑Tuning (PEFT) approaches such as LoRA, prefix tuning, adapters, and quantization‑aware training.
• Proficiency in PyTorch, TensorFlow, Hugging Face ecosystem, and good to have distributed training frameworks (e. g., DeepSpeed, PyTorch Lightning, Ray).
• Basic understanding of MLOps best practices, including experiment tracking, model versioning, CI/CD for ML pipelines, and deployment in production environments.
• Experience working with large datasets, feature engineering, and data pipelines, leveraging tools such as Spark, Databricks, or cloud‑native ML services (AWS Sagemaker, GCP Vertex AI or Azure ML).
• Knowledge of GPU/TPU optimization, mixed precision training, and scaling ML workloads on cloud or HPC environments.
• Applied Problem‑Solving

Mandatory Skill

• Demonstrated success in adapting foundation models to domain‑specific applications through fine‑tuning or transfer learning. Mandatory skill –
• Strong ability to design, evaluate, and improve models using robust validation strategies, bias/fairness checks, and performance optimization techniques.
• Experience in working on applied AI problems across NLP, computer vision, multimodal systems, or any other domain.
• Proven ability to lead and mentor a team of applied scientists and ML engineers, providing technical guidance and fostering innovation.
• Strong cross‑functional collaboration skills to work with product, engineering, and business stakeholders to deliver impactful AI solutions.
• Ability to translate cutting‑edge research into practical, scalable solutions that meet real‑world business needs.

Other

• Excellent communication and presentation skills to articulate complex ML concepts to both technical and non‑technical audiences.
• Continuous learner with awareness of emerging trends in generative AI, foundation models, and efficient ML techniques.

Education & Experience

• Master's or Ph. D. in Computer Science, Machine Learning, Data Science, Statistics, or a related field.
• 7+ years of hands‑on experience in applied machine learning and data science, with at least 2+ years in a leadership or managerial role.