Senior Data Scientist – AI

Job Description: Senior Data Scientist – AI

Location: Gurgaon / Jaipur (On-site with occasional client visits across NCR and India)

Company: SoftSensor AI

About SoftSensor AI

SoftSensor AI develops AI-powered enterprise solutions, including document intelligence platforms, decision-support systems, optimization engines, and domain-specific copilots. We combine Machine Learning, Large Language Models (LLMs), cloud technologies, and modern software engineering practices to deliver production-grade AI applications.

Position Overview

We are seeking a highly motivated Senior Data Scientist – AI to lead the design, development, deployment, and continuous improvement of AI and machine learning solutions. This role requires strong expertise in machine learning, generative AI, MLOps, and cloud deployment, along with the ability to translate business challenges into scalable AI products.

The ideal candidate is a hands-on practitioner who enjoys building end-to-end AI systems, collaborating with cross-functional teams, and mentoring junior team members.

Key ResponsibilitiesAI Solution Design & Architecture

• Understand business problems and convert them into scalable AI solution designs.
• Evaluate and recommend suitable approaches including traditional ML, Generative AI, RAG, agentic workflows, and hybrid architectures.
• Define KPIs, success metrics, and evaluation frameworks for AI initiatives.

Machine Learning & Generative AI Development

• Build and deploy supervised and unsupervised ML models for classification, regression, forecasting, clustering, and ranking.
• Design and implement LLM-based applications, including:
• Retrieval-Augmented Generation (RAG)
• AI Assistants and Copilots
• Agentic Workflows
• Prompt Engineering and Evaluation
• Develop robust testing and benchmarking frameworks for model performance.

Production Deployment & MLOps

• Collaborate with engineering teams to deploy AI models as scalable APIs and microservices.
• Implement best practices for:
• Model versioning
• CI/CD pipelines
• Monitoring and alerting
• Drift detection
• Experiment tracking
• Ensure performance, security, reliability, and scalability of deployed solutions.

Data Strategy & Experimentation

• Define data requirements, annotation processes, and labeling standards.
• Lead experiments including A/B testing, pilot deployments, and performance evaluations.
• Work with data engineering teams to build pipelines supporting production AI systems.

Leadership & Stakeholder Management

• Present technical concepts and recommendations to both technical and non-technical stakeholders.
• Mentor junior data scientists and ML engineers.
• Support client solutioning, PoCs, demos, and pre-sales activities.

Required Qualifications

• Bachelor's or Master's degree in Computer Science, Data Science, AI, Statistics, Mathematics, or a related field.
• 5–10 years of experience in Machine Learning, Data Science, or Applied AI.
• Minimum 3 years of experience delivering AI solutions from problem definition to production deployment.
• Strong programming skills in Python.
• Hands-on experience with:
• Pandas, NumPy
• Scikit-learn
• PyTorch and/or TensorFlow
• FastAPI or Flask
• Strong understanding of:
• ML algorithms
• Statistical analysis
• Experimental design
• Model evaluation techniques
• Experience deploying production-grade ML or AI systems.
• Ability to work closely with engineering, product, and business stakeholders.

Preferred Qualifications

• Experience with Generative AI and LLM platforms.
• Hands-on experience with Azure OpenAI, Azure AI Services, AWS Bedrock, or similar platforms.
• Experience with vector databases such as Pinecone, Qdrant, FAISS, or Elasticsearch.
• Familiarity with MLOps tools including MLflow, Azure ML, SageMaker, or Weights & Biases.
• Exposure to React, Next.js, or AI-enabled front-end applications.
• Experience in enterprise domains such as Banking, Insurance, Healthcare, Manufacturing, Logistics, or Government.

What Success Looks Like

Within the first 6–9 months, you will

• Lead deployment of one or more production AI solutions delivering measurable business impact.
• Own AI features actively used by end users.
• Establish monitoring and evaluation frameworks for AI quality, latency, and reliability.
• Become a subject matter expert in a core capability area such as RAG, Recommendation Systems, Forecasting, Optimization, or AI Agents.

Why Join SoftSensor AI?