Machine Learning Engineer

This is a fully remote position, open to applicants in India.

📋 Description

• Conduct research, design, train, and deploy deep learning models for various applications in speech/audio (including ASR, speaker diarization, audio classification, TTS, and noise suppression) as well as computer vision (such as detection, segmentation, classification, and video understanding).

• Develop training pipelines that efficiently manage large-scale datasets, including data preprocessing, augmentation, and versioning workflows.

• Choose and modify cutting-edge architectures (like Transformers, CNNs, RNNs, diffusion models, etc.) and fine-tune or distill pre-trained models to meet production constraints.

• Enhance models for inference by applying techniques such as quantization, pruning, and knowledge distillation, focusing on latency, throughput, and memory budgets across CPU/GPU/edge hardware.

• Collaborate with software engineers to integrate models into production systems, and design APIs and microservices for effective model serving.

• Establish and monitor evaluation benchmarks, track model performance in production, and foster continuous improvement cycles.

• Stay abreast of relevant research literature, assess and implement applicable state-of-the-art techniques, and contribute to internal technical forums.

⛳️ Requirements

• B.Tech / M.Tech / M.Sc. / PhD in Computer Science, Electrical Engineering, Signal Processing, or a related discipline.

• Over 4 years of experience in machine learning/deep learning engineering with substantial hands-on involvement in speech/audio and/or computer vision within production settings.

• Proficiency in PyTorch (primary) and TensorFlow/Keras, with familiarity in JAX considered an advantage.

• In-depth knowledge of Wav2Vec 2.0, Whisper, ESPnet, SpeechBrain, torchaudio, and librosa.

• Extensive experience with speech/audio frameworks and toolkits: YOLO, DETR, ViT, EfficientNet, SAM, and standard CV pipelines (OpenCV, torchvision, Albumentations).

• Strong foundation in computer vision technologies: TensorRT, ONNX Runtime, TorchScript, DeepSpeed, or Triton Inference Server.

• Practical experience in model inference optimization using Python and solid software engineering principles: OOP, clean code, testing, and CI/CD.

• Competent in SQL for data extraction and pipeline logging.

• Familiarity with distributed training frameworks (DDP, DeepSpeed, FSDP) and large-scale data pipelines.

• Knowledge of cloud ML platforms (AWS SageMaker, GCP Vertex AI, Azure ML) and containerized deployment technologies (Docker, Kubernetes, ECS).

• Strong understanding of system design principles for ML services, including throughput, latency, scalability, and fault tolerance.

🏝️ Benefits

• Professional growth in a dynamic, rapidly expanding, high-social-impact industry.

• An open-minded, collaborative culture comprised of enthusiastic colleagues who are motivated by the challenge of innovation aimed at making a significant impact on people and the planet.

• A truly multicultural experience: You will have the opportunity to work with and learn from individuals from diverse geographies, nationalities, and backgrounds.

• Structured, tailored learning and development programs designed to enhance your leadership, management, and professional skills through the Sun King Center for Leadership.