About the role
Please work on the below req and share 3 good CV by 5:00 PM
Job Title: Data Scientist (AI/ML/GenAI)
Experience: 2–5 years Location: [Hyderabad | Bangalore] Job Type: Full-time Work Mode: [On-site / Hybrid / Remote]
---
About the Role
We are looking for a highly motivated and hands-on Data Scientist to join our AI & Data Science team within an engineering services environment. The ideal candidate will have a strong foundation in data science and machine learning, with practical experience in building and deploying AI/ML/GenAI solutions across cloud and on-premises infrastructures.
---
Key Responsibilities
· Design, develop, and deploy AI/ML models for various industrial and engineering use cases, including:
o Statistical models, classical ML, deep learning, and prescriptive analytics
o Computer Vision models for image/video analytics
o NLP models for text-based insights
o GenAI models for content generation, summarization, knowledge extraction, etc.
· Collaborate with domain experts and engineering teams to translate business problems into data science solutions.
· Build and manage data pipelines and perform data wrangling, feature engineering, and data quality checks.
· Develop and expose AI services using RESTful APIs for integration with enterprise applications.
· Deploy and monitor models in both on-premise environments and cloud platforms (Azure, AWS).
· Apply MLOps best practices for versioning, monitoring, and automation.
· Stay updated on the latest trends in AI, ML, and GenAI and assess their applicability to engineering scenarios.
---
Required Skills & Experience
· 3–5 years of hands-on experience in building and deploying ML/DL models in real-world projects.
· Strong experience with:
o Python, Scikit-learn, TensorFlow, PyTorch
o OpenCV, Transformers (HuggingFace), LangChain or similar GenAI frameworks
o SQL and data manipulation libraries (Pandas, NumPy)
· Exposure to GenAI platforms and techniques (e.g., LLMs, prompt engineering, embeddings, RAG pipelines).
· Experience in data engineering: data ingestion, preprocessing, storage (structured and unstructured).
· Proven ability to deploy models on cloud platforms—preferably Azure or AWS—using services like SageMaker, Azure ML, Lambda, or Kubernetes.
· Experience in building and exposing APIs (e.g., Flask, FastAPI).
· Good understanding of deploying AI solutions in resource-constrained on-prem environments.
· Familiarity with DevOps or MLOps tools (e.g., MLflow, DVC, Git, Docker, CI/CD pipelines) is a plus.
---
Qualifications
· Bachelor's or Master’s degree in Engineering, Computer Science, Data Science, or a related field.
· Relevant certifications in Cloud (AWS, Azure) and AI/ML technologies will be an advantage.
---
Preferred Attributes
· Experience working in engineering or industrial domains (Aerospace, Rail, MedTech, etc.)
· Strong problem-solving skills with the ability to work independently and collaboratively.
· Excellent communication skills to engage with cross-functional teams and stakeholders.