Machine Learning Lead

Company Introduction
Varaha is a global, leading climate-tech venture focused on carbon removal solutions such as regenerative agriculture, afforestation, biochar, and enhanced rock weathering supporting smallholder land stewards at scale. In just our third year of operation, we are removing and avoiding more than 1 million tons of CO?, distributing the majority of revenues to over 100,000 smallholder land stewards in South Asia and Sub-Saharan Africa. Backed by leading global investors, our founding and management team has a stellar track record of scaling impactful projects and products across agri-tech and sustainability sectors.
Position: Machine Learning lead
About The Role
We are seeking a Machine Learning Lead with deep expertise in applying ML/AI to complex real-world challenges, with preference towards geospatial and climate data solutions. You will be responsible for defining and executing our ML/AI strategy, building and managing a high-performing team of ML Engineers and Data Scientists, and driving company-wide adoption of ML tools and models to enhance our carbon intelligence platform, field operations, and verification processes. This role requires 6-10 years of experience or more in the ML/AI domain.
Responsibilities

• Identify and uncover new use cases for ML/AI across Varahas business, from carbon estimation and geospatial analysis to operational efficiency for field agents.
• Drive the adoption of ML tools and best practices across engineering and data science teams, establishing MLOps pipelines for scalable model deployment and monitoring.
• Lead the architecture and development of scalable, resilient ML systems for processing high-throughput geospatial and carbon data.
• Build and manage a team of Machine Learning Engineers and Data Scientists, fostering a culture of innovation, rigor, and production-readiness.
• Collaborate with product, engineering, and operations teams to embed ML capabilities into core products and internal tools.
• Oversee model lifecycle management, including experimentation, training, validation, deployment, and performance monitoring in a production environment.
  

Skills & Qualifications

• 6-10+ years of experience in Machine Learning, Data Science, or a related field, with a focus on real-world application and deployment.
• Proven experience in building, mentoring, and managing a technical team (ML Engineers/Data Scientists).
• Strong knowledge of MLOps, system design for distributed ML pipelines, and cloud-native services (AWS, GCP, or Azure).
• Deep proficiency in machine learning frameworks, libraries, and best practices (Python, PyTorch, TensorFlow, etc.).
• Experience with large-scale data processing, data modeling, and feature engineering for complex datasets, especially geospatial data.

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  Demonstrated ability to translate vague business problems into structured, high-impact ML solutions and drive their adoption.
  

Bonus Points If You Have

• Advanced experience with geospatial data processing (Satellite imagery, GDAL, rasterio, GeoJSON, etc.) or remote sensing.
• Familiarity with real-time stream processing for ML features (Kafka, Redis Streams).
• Experience in climate-tech, agriculture, sustainability domains, or a background of ML / CV / Geo-Spatial research groups in renowned institutions like IISc, IIT Bombay, IIIT Bangalore, Microsoft Research, Google Research, etc.
  

What We Offer
Join a small, ambitious, and international team and enjoy the following benefits:

• Competitive salary and benefits package (ESOP)
• Key role in shaping a fast-growing climate tech startup
• Support for learning & professional development
• A culture of undogmatic, unbureaucratic creativity and collaboration
  

Please note this job description is not designed to contain a comprehensive listing of activities, duties, or responsibilities that are required of the employee for this job. Duties, responsibilities, and activities may change at any time with or without notice.
Varaha is an Equal Opportunity Employer. This company does not discriminate in employment and personnel practices based on race, sex, age, handicap, religion, national origin or any other basis prohibited by applicable law. Hiring, transferring and promotion practices are performed without regard to the above listed items.
If you are interested in becoming a part of this venture, then we would love to know your story, write to us at [HIDDEN TEXT]