Machine Learning Strategist

1 week ago


Pune, India Cybage Software Full time

Role OverviewCybage 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 ResponsibilitiesPractice 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.QualificationsExperience- 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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