Machine Learning Engineer

What you will be expected to do

• Research, design, train, and productionize deep learning models for speech/audio (ASR, speaker diarization, audio classification, TTS, noise suppression) and computer vision (detection, segmentation, classification, video understanding) use cases.
• Architect training pipelines capable of handling large-scale datasets, manage data preprocessing, augmentation, and versioning workflows.
• Select and adapt state-of-the-art architectures (Transformers, CNNs, RNNs, diffusion models, etc.) and fine-tune or distill pre-trained models for production constraints.
• Optimize models for inference - quantization, pruning, knowledge distillation - targeting latency, throughput, and memory budgets on CPU/GPU/edge hardware.
• Work with software engineers to integrate models into production systems, design APIs and microservices for model serving.
• Define and track evaluation benchmarks, monitor model performance in production, and drive continuous improvement cycles.
• Stay current with research literature, evaluate and implement relevant SOTA techniques, contribute to internal technical forums.

You might be a strong candidate if you have/are

• B.Tech / M.Tech / M.Sc. / PhD in Computer Science, Electrical Engineering, Signal Processing, or a related field.
• 4+ years of experience in machine learning/deep learning engineering with significant hands-on work in speech/audio and/or computer vision in production environments.
• PyTorch (primary) and TensorFlow/Keras, familiarity with JAX is a plus.
• Deep expertise in Wav2Vec 2.0, Whisper, ESPnet, SpeechBrain, torchaudio, librosa.
• Strong experience with speech/audio frameworks and toolkits: YOLO, DETR, ViT, EfficientNet, SAM, and standard CV pipelines (OpenCV, torchvision, Albumentations).
• Solid background in computer vision: TensorRT, ONNX Runtime, TorchScript, DeepSpeed, or Triton Inference Server.
• Hands-on experience with model inference optimization using Python and strong software engineering fundamentals: OOP, clean code, testing, CI/CD.
• Proficient in SQL for data extraction and pipeline logging. 
• Experience with distributed training frameworks (DDP, DeepSpeed, FSDP) and large-scale data pipelines.
• Familiarity with cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployment (Docker, Kubernetes, ECS).
• Good knowledge of system design principles for ML services: throughput, latency, scalability, fault tolerance.

What Sun King offers

• Professional growth in a dynamic, rapidly expanding, high-social-impact industry
• An open-minded, collaborative culture made up of enthusiastic colleagues who are driven by the challenge of innovation towards profound impact on people and the planet.
• A truly multicultural experience: You will have the chance to work with and learn from people from different geographies, nationalities, and backgrounds.
• Structured, tailored learning and development programs that help you become a better leader, manager, and professional through the Sun King Center for Leadership.

About
Sun King is the world’s leading off-grid solar energy company, combining cutting-edge product design, fintech, and field operations to deliver energy access for the 1.8 billion people who live without an affordable and reliable electric-grid connection.Sun King has built a new kind of energy utility: distributed, green, customer-centric, and affordable. We bring clean, reliable, decentralized energy directly into people’s lives — from solar kits that provide first-time energy access to multi-kilowatt systems that serve both off-grid users and grid-connected customers powering larger homes, schools, hospitals, farms, offices, and light manufacturing.Already, 25 million homes and businesses rely on Sun King for electricity supply and the appliances and services it enables: lighting, televisions, fans, refrigeration, and smartphones. Sun King combines energy generation, energy-efficient appliances, installation, and financing into one seamless offering. Think of it as a distributed utility, designed for wherever energy is needed and designed to scale with its users as incomes and energy needs grow.Sun King makes solar products affordable to low-income households and businesses via ‘pay-as-you-go’ (PAYG) purchase financing. Sun King installs solar after customers pay a small deposit. Customers then make small, manageable payments of as little as US $0.14 a day via mobile money or cash.Instead of paying for expensive, polluting, and health-damaging kerosene for lighting or diesel for power, customers unlock savings through accessing solar power and after one to two years of payments, customers own their solar equipment outright.Sun King collects payments digitally through mobile money systems and its 35,000 field agents — over 1 million payments each day. To date, Sun King has extended more than $1.4 billion in PAYG loans to customers.Sun King began by powering homes and businesses with solar systems delivered through PAYG financing. Now, we’re using the same model to make smartphones and clean cooking equipment affordable: helping households connect to the digital economy and transition from wood-based fuels to modern, sustainable alternatives.Sun King employs 3,500 full-time staff in 14 countries, with specialties spanning product design, data science, logistics, customer service, sales, software, operations, and more — all with a passion to serve off-grid families. Sun King is committed to gender diversity in the workplace. Women represent 42% of Sun King’s workforce.