AI / ML Team Leader

WonderBiz Technologies Pvt. Ltd.; Thane; On-site; INR 2,800,000 - 4,500,000; Full time

Job summary

WonderBiz Technologies Pvt. Ltd. in Maharashtra, Thane is seeking an AI/ML Team Leader to steer a DS team while remaining hands-on in building and shipping production-grade ML for industrial systems.

You will handle end-to-end lifecycle from framing to deployment and monitoring, with a strong emphasis on time-series data and multimodal inputs. You will also lead and grow the team, define roadmaps for anomaly detection, asset health, and closed-loop decisioning, and advance IP related to

Qualifications

• 8+ years in applied AI/ML technologies
• 2+ years leading teams (hiring, mentorship, performance management)
• Strong Python and engineering fundamentals (clean code, testing)
• Experience shipping AI/ML solutions in production (MLOps, monitoring, drift, retraining)

Responsibilities

• Own end-to-end lifecycle: problem framing → data readiness → modeling → deployment → monitoring → iteration
• Define and execute roadmap areas like anomaly detection, asset health, optimization, closed-loop decision support
• Build scalable foundations for baselines, drift detection, model observability, incident response
• Lead and mentor DS talent, set processes, frameworks and quality standards
• Develop and deploy AI/ML solutions in production, with deployment ownership and performance validation
• Identify and progress patentable innovations tied to closed-loop autonomy and production deployment

Skills

Time-series ML

Team leadership

Python programming

MLOps

Deployment of models

Communication

Education

B.Tech/B.E. in any specialization

Job description

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

Role:

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).

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, postmortems).


• Build and deploy AI / ML solutions / models in production.Own deployment,monitoring, performance validation, and iteration of models in production


• Identify, document, and progress patentable innovations tied to closed-loop autonomy and production deployment.

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 [Ex: Frequency-domain time-series techniques (FFT/spectral analysis) and control/optimization methods (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