Senior Machine Learning Engineer
4 weeks ago
Mandatory GuidelinesTarget folks having 5+ years of work expSkills -
Python, Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent, Proficiency with ML modeling frameworks (PyTorch, Tensorflow, etc.), Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)Target Industry/Company: Look for folks from product companies only preferred SpaceTechs, Defense, and Aerospace domain companiesEducation - BE/BTech/ME/MCA/MTech/MSc only and specialization preferred in DS/ML/Applied Sciences/Statistics/AI/Earth System Sciences/Optical Engineering/Materials Science/Avionics/Aerospace/Engineering Physics/Control Systems/CS/IT/IS from reputed organizationsJoining Availability: Maximum NP of 45 days will be considered.Strictly avoid folks asking for a 100% hikeAvoid Offer shoppers, Share the only candidates having valid reasons to look for other offers.Interview Process: 4 rounds1 Screening/Introductory call with HM - DivyaThe candidate is expected to be prepared with an Introduction presentation capturing Basic details such as Career journey, Educational background, Interest in Satsure, etcMaximum 3 Technical discussion rounds.PerksRelocation bonus of 25k
Roles & ResponsibilitiesAbout SatSureSatSure is a deep tech, decision Intelligence company that works primarily at the nexus of agriculture, infrastructure, and climate action creating an impact for the other millions, focusing on the developing world. We want to make insights from earth observation data accessible to all.If you are interested in working in an environment that focuses on the impact on society, driven by cutting-edge technology, and where you will have the freedom to work on innovative ideas and be creative with no hierarchies, SatSure is the place for you.Roles and ResponsibilitiesArchitect, build and integrate end-to-end life cycles of large-scale, distributed machine learning systems i.e. ML Ops using cutting-edge tools/frameworks.Develop tools and services for the explainability of ML solutions.Implement distributed cloud GPU training approaches for deep learning models.Build software/tools that improve the rate of experimentation for the research team and extract insights from it.Identify and evaluate new patterns and technologies to improve the performance, maintainability, and elegance of our machine learning systems.Lead and execute technical projects to completion. Communicate with peers to build requirements and track progress.Mentor fellow engineers in your areas of expertise - Contribute to a team culture that values effective collaboration, technical excellence, and innovation.Collaborate with engineers across various functions to solve complex data problems at scale.RequirementsExperience5+ years of professional experience in implementing MLOps framework to scale up ML in production.Hands-on experience with Kubernetes, Kubeflow, MLflow, Sagemaker, and other ML model experiment management tools including training, inference, and evaluation.Experience in ML model serving (TorchServe, TensorFlow Serving, NVIDIA Triton inference server, etc.)Proficiency with ML model training frameworks (PyTorch, Pytorch Lightning, Tensorflow, etc.).Experience with GPU computing to do data and model training parallelism.Solid software engineering skills in developing systems for production.Strong expertise in Python.Building end-to-end data systems as an ML Engineer, Platform Engineer, or equivalent.Experience working with cloud data processing technologies (S3, ECR, Lambda, AWS, Spark, Dask, ElasticSearch, Presto, SQL, etc.).Having Geospatial / Remote sensing experience is a plus.Competencies:Excellent debugging and critical thinking skills.Excellent analytical and problem-solving skills.Ability to work in a fast-paced, team-based environment.Educational Qualifications:Bachelors, Master, or Ph.D. Degree in Computer Science/Machine Learning, SW Engineering.BenefitsWhy Us?Opportunity to work on a unique and
futuristic technology setupFlat organizational structure and accessibilityBest in-class leave policyAdditional allowances for learning, skill development, broadband, medical insurance cover, etc.
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