Intern - ML Engineer
2 days ago
#ABOUT 360WATTS:We lay path towards energy self-dependence of residential consumers. We digitise the home energy. How? our goal is to accelerate solar adoption by removing every barrier — cost, complexity, and uncertainty. We offer flexible ways to own or subscribe, complete transparency on energy and savings, and automation that makes solar simple to operate and maintain. Today we enable homes to go solar with ease. Tomorrow, these homes will be an active part of an intelligent energy system with no power cuts, cheap electricity, and sustainable for the future generations.#YOUR ROLE:This is a 6-months paid internship. As a Machine Learning Intern, you'll work closely with our AI Software Engineer and IoT Systems Engineer to explore and integrate machine learning models into real-world solar + energy IoT systems.In short, you'll have to focus on model scouting & integration,data preparation,lightweight ML at the edge, and practical workflows that connect energy data to meaningful user experiences - working together on a prototype development. In the end, you will help to develop hybrid/in-house early-stage predictive models to maximise solar performance, fault detection and integrate use-cases of smart-home automation.#YOUR RESPONSIBILITIES:>> Model Scouting, Integration & DeploymentConvert trained ML models into lightweight formats (TensorFlow Lite, ONNX)Deploy models on edge devices (Raspberry Pi, Jetson Nano, ESP32) and test inference performanceImplement OTA (over-the-air) update workflows for ML models>> Data Handling & Pre-processingAssist in preparing time-series energy datasets (solar generation, consumption, weather)Use open-source tools (Label Studio or similar) to annotate or validate datasetsWork with the team to ensure clean, AI-ready data pipelines>> Experimentation & PrototypingExplore baseline ML techniques for forecasting (solar output, load demand) and anomaly detectionBenchmark edge vs cloud inference performance (latency, accuracy, resource usage)Document experiments and share learnings with the team#ELIGIBILITY: EducationPost-grad Bachelors or Masters in Computer Science, AI/ML, Data Science>>Skills (must-have)Python (NumPy, Pandas, scikit-learn)Basic ML model training (classification, regression, time-series)Familiarity with ML Frameworks (TensorFlow or PyTorch)Project experience in ML during coursework or internships (e.g., competition, academic project, Kaggle/GitHub repo)Self-initiative, ability to learn fast>> Skills (good-to-have)Edge deployment experience (TFLite, ONNX Runtime)Knowledge of IoT protocols (MQTT, Modbus)Git/GitHub, Docker basics#YOU WILL GAIN:Be part of a founding-stage team shaping the future of decentralized energy systemOpportunity to transition into a full-time ML Engineer roleHands-on experience in end-to-end ML workflows — from scouting existing models to deploying them on edge (and cloud)Exposure to real-world IoT + energy data and how AI transforms solar performance#JOB DETAILS:Potential start = immediate or from Salary = Rs. 10k per monthOn-site (office) in Coimbatore (near Codissia)Duration = 3 to 6 months (with option to transition into future FT role, upon developing required skillsets)Apply here in LinkedIn. High preference will be given to application with links to past projects. Good luck
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