Senior Machine Learning (ML) Engineer

Brief DescriptionJob Overview TenureFull-time, Permanent LocationWork from office, Trivandrum QualificationMaster’s or PhD in computer science or equivalent degree OfferCompetitive salary and stock award Job Description The position of Senior ML engineer at Eartheye Space is critical to the company’s famed feeds offering. This role requires the selected candidate to develop machine learning models. Reporting to the head of software, you work with a team of junior computer vision (CV)/ machine learning (ML) engineers. Eartheye Space is a fast-paced organisation, and you will be accountable for the timely delivery of well-performing models. You will also mentor and assist the junior engineers working alongside you. Why join the Eartheye Space team?

Cutting-edge technology work: an opportunity to work in ground-breaking Earth observation technologies and datasets—imaging and non-imaging—in a cloud environment. Career growth: An exciting category-creating company entering a rapid growth phase, which means many job openings and career growth opportunities for the core team members Employee equity: Early-stage equity and stock options can experience significant value growth in the next rounds of funding and growth Global mobility: With an international client base, there will be transfer opportunities as the company grows internationally Mission and the Journey: Building a high-performing company on the foundation of: (I) Delighted customers, (II) High-performing teams, (III) Innovative products, (IV) Stellar results. Preferred SkillsWork Experience You should have:

At least three years of software development and two years of CV/ML model development Managed a team size of at least five members doing ML work Hands-on experience with supervised and unsupervised learning methods, with working knowledge in segmentation, classification and object detection methods Worked with satellite data and have a working knowledge of remote sensing and GIS Expert knowledge of Python programming Delivered under tight deadlines Worked in an agile environment with constant change Clear communication skills—both spoken and written English