Data Science Manager

Skyleaf Consultants LLP
Noida, Uttar Pradesh, India
  • ML & AI System Design and Development, Model Tuning
  •  Design and implement machine learning solutions using a mix of classical ML models
  • and LLM-based approaches.
  •  Select appropriate techniques for each problem, balancing accuracy, performance, cost,
  • and operational complexity.
  •  Build and train models for tasks such as classification, similarity matching, extraction,
  • normalization, and ranking.
  • Should have experience on Model Tuning
  • Should have experience on AWS.
  •  Develop LLM workflows including embeddings, prompt design, and retrieval-augmented
  • generation where applicable.
  •  Own data preparation for ML workloads, including data profiling, cleansing,
  • deduplication, labeling, and validation.
  •  Work with structured and unstructured datasets across relational databases, data lakes,
  • and document sources.
  •  Define and maintain training, evaluation, and inference datasets to support reliable model
  • performance.
  •  Integrate ML and LLM inference into Java/Spring backend services via APIs, async
  • workflows, or batch processes.
  •  Deploy and operate ML services on AWS using containers and managed services.
  •  Implement model versioning, experiment tracking, monitoring, and retraining processes.
  •  Ensure reliability, scalability, and observability of ML systems in production.
  • Technical Ownership and Collaboration
  •  Act as a senior technical contributor for ML and AI-related design and implementation
  • decisions.
  •  Collaborate closely with backend, data, and platform engineers to deliver production-
  • ready systems.
  •  Define and standardize engineering practices for building, deploying, and operating ML
  • and LLM systems in production.
  •  Provide guidance on when ML or LLM approaches are appropriate versus simpler
  • alternatives.
  • • Required Qualifications
  •  Bachelor’s or Master’s degree in Computer Science, Engineering, Data Science,
  • or a related field.
  •  5+ years of experience building and deploying ML systems in production and Model Tuning.
  •  Strong Python skills with hands-on experience in classical ML frameworks and
  • modern ML tooling.
  •  Solid understanding of statistics, ML algorithms, and model evaluation
  • techniques.
  •  Experience working with data pipelines, data quality issues, and large datasets.
  •  Familiarity with LLM concepts such as embeddings, prompt design, and RAG-
  • style architectures.
  •  Experience integrating ML systems into backend services and cloud
  • environments (AWS preferred).
  •  Ability to collaborate effectively with Java/Spring backend and platform teams.
  • • Preferred / Nice-to-Have
  •  Experience with NLP or text-heavy ML problems.
  •  Hands-on exposure to open-source or hosted LLMs and vector search systems.
  •  Experience with hybrid ML systems combining rules, models, and LLMs.
  •  Prior experience in enterprise or B2B SaaS platforms.

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