Bachelor’s or Master’s degree in Computer Science, Artificial Intelligence, Data Science, or a related field
5–8+ years of experience in AI/ML Engineering
At least 3 years in applied deep learning
Requirements:
Architect, develop, and deploy ML models for multimodal problems
Own the complete ML lifecycle
Leverage transfer learning and self-supervised approaches
Design and implement scalable training pipelines and inference APIs
Collaborate with MLOps and data engineering to productionize models
Continuously monitor model performance and implement retraining workflows
Stay updated on cutting-edge AI research
Write clean and reusable code
Job description
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, Data Science, or a related field.
5–8+ 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.
