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