Lead Data Scientist

Job Description

Key Responsibilities :

As a Lead Data Scientist Computer Vision, you will :

– Own technical charters and roadmap for multiple ML/CV initiatives.

– Lead and mentor applied scientists, mapping complex EO problems into actionable, scalable technical solutions.

– Drive hypothesis generation, experimentation, architecture design, model development, and deployment for production ML pipelines.

– Own E2E delivery of large-scale ML/CV systems from problem framing to data design, model development, deployment, and monitoring.

– Collaborate with Product, MLOps, Platform, and Geospatial experts to convert ambiguous requirements into elegant solutions.

– Communicate technical findings to leadership, customers, and cross-functional partners with clarity and precision.

– Assist data science managers in effective project, resource management, and timely deliverables (in an agile manner), via showcasing strong sense of ownership and accountability.

– Build reliable, efficient models that scale across geographies, seasons, sensors, and business domains.

– Write clean, scalable production-grade code in Python/PyTorch.

– Conduct A/B experiments and calibrate ML metrics to business KPIs.

– Innovate on model architectures (Transformers, diffusion, generative, time-series models, self-supervision, multimodal fusion and temporal modeling) to advance in-house geospatial ML SOTA.

– Represent your work through patents, technical documents, internal whitepapers, and publications (as applicable).

– Contribute to hiring and technical excellence, including mentoring junior team members and interns.

Experience :

Tech/MS (Research)/PhD in CS, EE, EC, Remote Sensing, or related fields preferably from leading academic/industrial labs/institutes/corporates.

Exceptional undergraduates with strong research/industry experience will also be considered.

Experience :

– 6+ years of applied ML/Computer Vision experience (industry preferred).

– 2+ years in a technical leadership role people and project leadership.

– Proven experience taking ML models from POC ? production ? monitoring.

Must have Technical Expertise :

To be eligible for this role, we are looking for candidates with the following qualifications :

– A proven track record of relevant experience in computer vision, NLP, learning theory, optimization, ML+Systems, foundational models, etc.

– Technically familiar with some, or most of (as evidenced by problem solving skills in novel scenarios) : Transformers, UNet, RNNs/LSTMs/GRUs, YOLO/RCNN/EncoderDecoder architectures, Generative models (GAN, VAE, Diffusion), Self-supervised & contrastive learning, Representation learning, domain adaptation & generalization, Semi-/Active learning, noisy-label learning, Super-resolution, anomaly detection, clustering, Model compression : distillation, pruning, quantization.

– PyTorch, Python, SQL, distributed systems (Spark), MLOps for large-scale training, data pipelines, and deployment.

Are you interested in this position?

Apply by clicking on the “Apply Now” button below!

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