<p><p><b>Job Description : </b></p><p><br/></p><p>We are seeking a high-impact AI/ML Engineer to lead the design, development, and deployment of machine learning and AI solutions across vision, audio, and language modalities.
</p><p><br/></p><p>You'll be part of a fast-paced, outcome-oriented AI & Analytics team, working alongside data scientists, engineers, and product leaders to transform business use cases into real-time, scalable AI systems.<br/><br/>This role demands strong technical leadership, a product mindset, and hands-on expertise in Computer Vision, Audio Intelligence, and Deep Learning.<br/><br/><b>Key Responsibilities : </b></p><p><br/></p><p>- Architect, develop, and deploy ML models for multimodal problems, including vision (image/video), audio (speech/sound), and NLP tasks.</p><p><br/></p><p>- Own the complete ML lifecycle : data ingestion, model development, experimentation, evaluation, deployment, and monitoring.<br/><br/></p><p>- Leverage transfer learning, foundation models, or self-supervised approaches where suitable.<br/><br/></p><p>- Design and implement scalable training pipelines and inference APIs using frameworks like </p><p>PyTorch or TensorFlow.<br/><br/></p><p>- Collaborate with MLOps, data engineering, and DevOps to productionize models using Docker, Kubernetes, or serverless infrastructure.<br/><br/></p><p>- Continuously monitor model performance and implement retraining workflows to ensure accuracy over time.<br/><br/></p><p>- Stay ahead of the curve on cutting-edge AI research (e.g., generative AI, video understanding, </p><p>audio embeddings) and incorporate innovations into production systems.<br/><br/></p><p>- Write clean, well-documented, and reusable code to support agile experimentation and long-</p><p>term platform : </b></p><p><br/></p><p>- Bachelors or Masters degree in Computer Science, Artificial Intelligence, Data Science, or a </p><p>related field.</p><p><br/></p><p>- 5 - 8+ years of experience in AI/ML Engineering, with at least 3 years in applied deep learning.</p><br/><b>Technical Skills : </b><br/><br/>- Languages : Expert in Python; good knowledge of R or Java is a plus.</p><p><br/>- ML/DL Frameworks : Proficient with PyTorch, TensorFlow, Scikit-learn, ONNX.</p><p><br/>- Computer Vision : Image classification, object detection, OCR, segmentation, tracking (YOLO, Detectron2, OpenCV, MediaPipe).<br/><br/></p><p>- Audio AI : Speech recognition (ASR), sound classification, audio embedding models (Wav2Vec2, Whisper, etc.).<br/><br/></p><p>- Data Engineering : Strong with Pandas, NumPy, SQL, and preprocessing pipelines for </p><p>structured and unstructured data.<br/><br/></p><p>- NLP/LLMs : Working knowledge of Transformers, BERT/LLAMA, Hugging Face ecosystem is preferred.<br/><br/></p><p>- Cloud & MLOps : Experience with AWS/GCP/Azure, MLFlow, SageMaker, Vertex AI, or Azure ML.<br/><br/></p><p>- Deployment & Infrastructure : Experience with Docker, Kubernetes, REST APIs, serverless ML </p><p>inference.<br/><br/></p><p>- CI/CD & Version Control : Git, DVC, ML pipelines, Jenkins, Airflow, etc.<br/><br/><p><b>Soft Skills & Competencies : </b></p><p><br/></p><p>- Strong analytical and systems thinking; able to break down business problems into ML </p><p>components.</p><p><br/></p>- Excellent communication skills able to explain models, results, and decisions to non-</p><p>technical stakeholders.<br/><br/></p><p>- Proven ability to work cross-functionally with designers, engineers, product managers, and </p><p>analysts.<br/><br/></p><p>- Demonstrated bias for action, rapid experimentation, and iterative delivery of impact.</p><br/></p> (ref:hirist.tech)