Data Science and Machine Learning Specialist

Posted 5 Days Ago
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4 Locations
In-Office
Senior level
Information Technology • Consulting
The Role
Lead design, development, and deployment of AI/ML solutions for sustainability, ESG, and H&S. Hands-on agent and LLM/BERT development, architect enterprise-grade systems, manage end-to-end ML lifecycle (data strategy, MLOps, production), advise senior clients, mentor teams, and ensure responsible AI, governance, and scalability.
Summary Generated by Built In
Job Description

Position: Senior AI/ML Specialist – Sustainability, Health & Safety

ERM is Senior AI/ML Specialist to lead the development of AI accelerators, intelligent agents, and machine learning models for sustainability, health, and safety domains. The role involves guiding teams in applying LLMs, BERT, and Microsoft Azure AI technologies to design enterprise-grade solutions and drive client impact.

At ERM, we combine deep domain expertise with a strong track record in delivering sustainability-focused digital solutions. Our Digital Services span the full information management lifecycle - from portfolio assessment, strategy, and technology evaluation to the design, testing, and implementation of enterprise-scale systems and cutting-edge technologies.

You will be part of a collaborative, innovation-driven environment that emphasizes technical excellence, scalability, and cross-functional teamwork to deliver solutions that address complex business challenges.

key Responsibilities:
  • Lead the design, development, and deployment of AI/ML solutions, accelerators, and frameworks that address client challenges in sustainability, ESG, and workplace safety.

  • Hands-on Experience in AI Agent development: demonstrable experience in agentic-AI development using Python, LangGraph, LangChain, and Model Context Protocol.

  • Architect LLM- and BERT-based applications, ensuring scalability, robustness, and security in enterprise environments.

  • Act as a trusted advisor to clients, engage with senior stakeholders to understand business needs, shape AI/ML strategy, and deliver impactful solutions.

  • Manage end-to-end AI/ML lifecycle - from solution scoping and data strategy to model development, MLOps, and production deployment.

  • Mentor and guide junior AI/ML professionals, fostering capability development within the team.

  • Collaborate with management consulting teams, domain experts, and technology architects to ensure business alignment and technical excellence.

  • Drive innovation initiatives, identifying opportunities to apply Generative AI, Responsible AI, and sustainability-focused analytics.

  • Contribute to thought leadership through publications, internal assets, and client workshops.

  • Ensure adherence to data governance, ethics, and responsible AI principles in all solution deliveries.

key Requirements:
  • Education: Bachelor’s or Master’s degree in Computer Science, Data Science, AI/ML, Engineering, or related fields. PhD is a plus.

  • Experience: 6–8 years of AI/ML project delivery, including at least 2–3 years in leading teams or architecting solutions.

  • Proven experience in consulting or client-facing environments, with a track record of delivering AI/ML strategy and execution for enterprise clients.

  • Strong executive-level communication and presentation skills — ability to influence CxO stakeholders.

  • Demonstrated expertise in solution architecture, MLOps, and scaling AI/ML solutions in production.

  • Deep understanding of sustainability, ESG frameworks, or health & safety data ecosystems is strongly preferred.

  • Excellent interpersonal, leadership, and team management skills.

  • Strong business acumen with ability to bridge strategy, technology, and client needs.

Preferred techncial Skills & Tools
  • AI/ML Frameworks: Advanced experience with TensorFlow, PyTorch, Hugging Face Transformers (BERT, GPT, LLaMA, etc.).

  • Generative AI/LLM Engineering: Fine-tuning, prompt orchestration, RAG (retrieval augmented generation), embeddings, vector databases (FAISS, Pinecone, Azure Cognitive Search).

  • Microsoft Ecosystem: Azure AI, Azure ML, Azure OpenAI Service, Microsoft Fabric, Power BI, Azure Synapse.

  • MLOps & Cloud Deployment: MLflow, Kubeflow, Docker, Kubernetes, GitHub Actions, Azure DevOps.

  • Data & Analytics: Python, R, SQL, Spark, Databricks

  • Knowledge of Responsible AI principles, model governance, bias/fairness testing.

  • Familiarity with ESG reporting standards (GRI, SASB, ESRS) and safety analytics is an advantage.

Relevant Information:
  • Industry: Sustainability Consulting Services

  • Functional Area: Advisory

  • Role: AI/ML Consultant

  • Career Level: CL3

  • Number of Vacancies: One

  • Location: Bengaluru, Delhi, Kolkata, Mumbai

Skills Required

  • Bachelor's or Master's degree in Computer Science, Data Science, AI/ML, Engineering, or related field
  • 6-8 years of AI/ML project delivery experience, including 2-3 years leading teams or architecting solutions
  • Proven consulting or client-facing experience delivering AI/ML strategy and execution for enterprise clients
  • Executive-level communication and presentation skills with ability to influence CxO stakeholders
  • Hands-on experience in AI agent development using Python, LangGraph, LangChain, and Model Context Protocol
  • Experience architecting LLM- and BERT-based applications for scalable, robust, secure enterprise deployment
  • Demonstrated expertise in solution architecture, MLOps, and scaling AI/ML solutions in production
  • Ability to manage end-to-end AI/ML lifecycle: solution scoping, data strategy, model development, MLOps, production deployment
  • Knowledge and application of data governance, ethics, and responsible AI principles
  • Deep understanding of sustainability, ESG frameworks, or health & safety data ecosystems
  • Experience with AI/ML frameworks and tools: TensorFlow, PyTorch, Hugging Face Transformers, fine-tuning, prompt orchestration, RAG, embeddings, vector DBs (FAISS, Pinecone)
  • Experience with Microsoft Azure ecosystem: Azure AI, Azure ML, Azure OpenAI Service, Azure Cognitive Search, Microsoft Fabric, Azure Synapse, Power BI
  • MLOps & cloud deployment experience: MLflow, Kubeflow, Docker, Kubernetes, GitHub Actions, Azure DevOps
  • Data & analytics experience: Python, R, SQL, Spark, Databricks
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