The Role
Lead the design, development, deployment, and monitoring of scalable multimodal AI and machine learning systems across computer vision, audio, and NLP. Own the complete ML lifecycle, build training pipelines and inference APIs, productionize models with cloud and MLOps infrastructure, implement retraining workflows, and apply emerging techniques such as foundation models, generative AI, and self-supervised learning. Collaborate cross-functionally with engineering, product, data, and design teams to deliver business impact.
Summary Generated by Built In
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.
- 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.
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
Skills Required
- 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 of applied deep learning experience
- Expert-level Python programming
- Proficiency with PyTorch, TensorFlow, Scikit-learn, and ONNX
- Computer vision experience with image classification, object detection, OCR, segmentation, and tracking
- Experience with YOLO, Detectron2, OpenCV, or MediaPipe
- Audio AI experience, including speech recognition, sound classification, or audio embeddings
- Experience with Pandas, NumPy, SQL, and data preprocessing pipelines
- Working knowledge of Transformers, BERT or LLaMA, and the Hugging Face ecosystem
- Experience with AWS, GCP, or Azure and MLflow, SageMaker, Vertex AI, or Azure ML
- Experience with Docker, Kubernetes, REST APIs, and serverless ML inference
- Experience with Git, DVC, ML pipelines, Jenkins, or Airflow
- Good knowledge of R or Java
- Strong analytical, systems thinking, communication, and cross-functional collaboration skills
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The Company
What We Do
Omni Reach is a digital innovation partner providing AI, commerce, and cloud solutions to accelerate enterprise growth and lead transformation. It specializes in SAP Commerce Cloud, SAP/CPI, headless commerce, and AI-driven eCommerce cloud solutions with intelligent automation. The company also delivers data science, microservices, cloud, security, and digital transformation services across global markets for enterprise and consumer brands.
