Team Leader - Artificial Intelligence/Machine Learning

WonderBiz Technologies Pvt.; Mumbai; On-site; INR 1,800,000 - 3,600,000; Full time

Job summary

WonderBiz Technologies Pvt. Ltd. in Mumbai is seeking an experienced AI/ML Team Leader to drive end-to-end time-series ML solutions for industrial systems.

This hands-on role balances coding (roughly 70%) with people leadership (about 30%), delivering production-grade models to customers. You will mentor DS talent, shape roadmaps for anomaly detection, predictive maintenance, and closed-loop decisioning, and collaborate with domain SMEs to translate constraints into robust ML/optimization

Qualifications

• 8+ years in applied AI/ML with leadership experience.
• Strong Python fundamentals and production ML experience.
• Experience shipping ML solutions to production and collaborating with customers.

Responsibilities

• Own the end-to-end lifecycle: framing, data readiness, modeling, deployment, monitoring, iteration.
• Define and execute roadmap areas like anomaly detection, asset health, optimization, closed-loop support.
• Build scalable foundations for baselines, drift detection, observability, and incident response.
• Translate real process constraints into ML/optimization/decisioning solutions with SMEs.
• Lead and mentor DS talent, establish processes, reviews, and governance.
• Develop AI/ML solutions/models and own deployment and monitoring in production.

Skills

Time-series ML

Team leadership

MLOps

Python programming

Production ML deployment

Communication

Education

B.Tech/B.E. in Any Specialization

Job description

Job Opportunity AI / ML Team Leader (Work from office)

We're hiring a Leader for our Data Science (DS) team to deliver production-grade ML for industrial systems using time-series and multimodal data (sensor/SCADA/historian, events, maintenance logs, and images/video where relevant). This is a hands-on role where you'll spend most of your time building and shipping (roughly 70% IC), while also leading and growing the team (roughly 30% people leadership).

Role

You'll work closely with customers and domain SMEs, ship models to production, and evolve our concept from "models" to an autonomous decisioning system: forecasting - detection/diagnosis - optimization - closed-loop actions (with safety + governance). A key part of the role is advancing our unique IP in closed-loop autonomous operations.

What You’ll Do

• Own the end-to-end lifecycle: problem framing - data readiness - modeling - deployment - monitoring - iteration.
• Define and execute roadmap areas like anomaly/event detection, asset/process health, root-cause support, optimization, and closed-loop decision support.
• Build scalable foundations for baselines, drift detection, model observability, and incident response.
• Partner with industrial customers and SMEs to translate real process constraints into ML/optimization/decisioning solutions.
• Drive unsupervised/self-supervised initiatives (representations, clustering, change-point detection, weak supervision, active learning).
• Develop a practical Reinforcement Learning (RL)/decisioning strategy (offline/safe RL, constrained optimization, simulators/digital twins), with guarded rollout patterns.
• Lead and mentor DS talent, set processes, frameworks and quality standards (design/code reviews, documentation, post-mortems).
• Build and deploy AI/ML solutions/models in production.
• Own deployment, monitoring, performance validation, and iteration of models in production.

Qualifications

• 8+ years in applied AI/ML technologies, including 2+ years leading teams (hiring, mentorship, performance management).
• Deep experience with time-series ML at scale, ideally with messy industrial data (e.g., Frequency-domain time-series techniques like FFT/spectral analysis and control/optimization methods like MPC-like approaches).
• Proven track record of shipping and operating AI/ML solutions in production (MLOps, monitoring, drift, retraining, reliability).
• Strong Python and engineering fundamentals (clean code, testing, production patterns).
• Strong communication, comfortable working directly with customers and cross-functional teams.

Bonus Points

• Offline/safe RL, constrained optimization, and/or simulators/digital twins.
• Self-supervised learning or foundation-model approaches for industrial time-series and multimodal fusion.
• Robotics and/or Industrial domain experience (manufacturing, energy, chemicals, mining, utilities), including safety/uptime/latency/edge constraints.
• Closed-loop or human-in-the-loop decision systems with governance and guardrails.
• Experience contributing to IP strategy, invention disclosures, and patent filings.

Education

• UG: B.Tech/B.E. in Any Specialization.