Senior AI/ML Engineer

This is a remote position.
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

- Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, DataScience, or a related field.

- 5–8+ years of experience in AI/ML Engineering, with at least 3 years in applied deep learning.

Technical Skills
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Languages : Expert in Python; good knowledge of R or Java is a plus.

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ML/DL Frameworks: Proficient with PyTorch, TensorFlow, Scikit-learn, ONNX.

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Computer Vision: Image classification, object detection, OCR, segmentation, tracking (YOLO, Detectron2, OpenCV, MediaPipe).

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Audio AI: Speech recognition (ASR), sound classification, audio embedding models (Wav2Vec2, Whisper, etc.).

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Data Engineering: Strong with Pandas, NumPy, SQL, and preprocessing pipelines for structured and unstructured data.

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NLP/LLMs: Working knowledge of Transformers, BERT/LLAMA, Hugging Face ecosystem is preferred.

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Cloud & MLOps: Experience with AWS/GCP/Azure, MLFlow, SageMaker, Vertex AI, or Azure ML.

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Deployment & Infrastructure: Experience with Docker, Kubernetes, REST APIs, serverless ML inference.

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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.

Benefits

- Competitive compensation and full-time benefits.

- Opportunities for certification and professional growth.

- Flexible work hours and remote work options.

- Inclusive, innovative, and supportive team culture

Originally posted on Himalayas