Machine Learning Strategist

3 weeks ago

Pune Maharashtra India, Maharashtra Cybage Software Full time

Role Overview

Cybage is seeking a Practice Head for Machine Learning Systems to lead our AI/ML capability within the CDAI business unit. This is a strategic leadership role that blends deep technical expertise in applied ML systems with practice-building, client consulting, and outcome-based delivery experience.

The role requires someone who has built and scaled ML engineering practices in IT services or consulting environments, is able to guide solutioning at a technical level, and can also engage clients in executive workshops to define AI adoption roadmaps.

Key Responsibilities

Practice Leadership

  • Define the vision and roadmap for Cybage’s Machine Learning Systems practice, aligned with industry trends and client priorities.
  • Build offerings and frameworks across ML model development, deployment, MLOps, generative AI, and responsible AI governance.
  • Develop accelerators, reference architectures, and reusable assets to differentiate Cybage in the market.

Client Consulting & Business Growth

  • Lead consultative workshops with client executives to co-create ML/AI strategies, adoption roadmaps, and use-case portfolios.
  • Partner with sales and account teams to drive presales solutioning, proposal creation, and thought leadership.
  • Position Cybage as a strategic partner for ML-driven transformations that are measurable and outcome-driven.

Delivery Excellence

  • Oversee delivery of ML programs spanning PoCs, pilots, and scaled deployments across industries.
  • Ensure robust MLOps and governance practices for model lifecycle management, monitoring, retraining, and compliance.
  • Provide architectural and technical guidance on ML stacks (e.g., TensorFlow, PyTorch, Hugging Face, MLflow, AWS Sagemaker, Azure ML, GCP Vertex AI, Databricks ML).
  • Drive service-based and outcome-based engagement models, ensuring predictability and value delivery.

Team & Capability Building

  • Build and mentor a high-performing team of ML engineers, data scientists, and solution architects.
  • Develop future leaders with consulting and solutioning depth, not just technical skill.
  • Foster collaboration across adjacent practices (Big Data, Cloud, Platform Engineering) to deliver end-to-end AI solutions.

Qualifications

Experience

  • 15+ years in IT services or consulting, with 7+ years in ML/AI leadership or architecture roles.
  • Proven ability to establish or grow an ML/AI practice, including team building, offering development, and client engagement.
  • Experience with end-to-end ML lifecycle: data prep, feature engineering, model training, evaluation, deployment, monitoring.
  • Exposure to service delivery models (consulting, managed services, outcome-based).
  • Strong background in applied ML use cases (forecasting, personalization, anomaly detection, NLP, computer vision, GenAI).

Skills & Competencies

  • Technical bent: ability to deep-dive into ML architectures, pipelines, and MLOps practices.
  • Strategic mindset: connect ML initiatives to tangible business outcomes.
  • Leadership: experience in building practices and leading distributed teams (does not need to be at massive scale).
  • Client-facing presence: ability to run workshops, advise senior stakeholders, and simplify complex ML topics.
  • Knowledge of AI governance, ethics, and compliance (responsible AI, data privacy, bias mitigation).

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