- 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

.

-  Robust 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.

📌 Data Science Manager (Noida)
🏢 Skyleaf Consultants LLP
📍 Noida