Role overview

Qualifications

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.
Expert in Python; good knowledge of R or Java is a plus.
Proficient with PyTorch, TensorFlow, Scikit-learn, ONNX.

Responsibilities

Architect, develop, and deploy ML models for multimodal problems, including vision, audio, and NLP tasks.
Own the complete ML lifecycle: data ingestion, model development, experimentation, evaluation, deployment, and monitoring.
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.

Key facts

Remote from: Anywhere
Full time
Senior (5-10 years)
ML Ops Engineer
English

Other skills

Analytical Thinking
Communication
Collaboration
Adaptability

About the company

Omni Reach

Digital Transformation Consulting

Welcome to Omni Reach - Your Gateway to SAP Cloud Commerce Excellence!At Omni Reach, we stand as a pioneering force, dedicated to propelling e-commerce businesses through their pivotal growth stage with our unmatched SAP Commerce Cloud services. From the enchanting beaches of Florida, US, to the vibrant tech hub of Bangalore, India, our global footprint allows us to extend our exceptional solutions to clients across the world.Our dynamic team of SAP Commerce Cloud Professionals breathes life into the digital realms of commerce. We are more than just a company; we are a collective of visionaries who have mastered the art of turning possibilities into achievements.Navigating the ever-evolving landscape of e-commerce demands more than just innovation – it requires a symphony of precision and insight. Here at Omni Reach, we've orchestrated a team of trailblazers who hold the compass to commerce's future. Our professionals are not merely skilled; they are connoisseurs of transformation, armed with the wisdom to sculpt digital ventures into success stories.At the heart of our endeavor lies our commitment to empowering businesses with unparalleled SAP Commerce Cloud expertise. Our services encompass a spectrum of support, consultation, and guidance, all meticulously designed to optimize your commerce journey. We understand that every digital footprint is unique, which is why our solutions are crafted like pieces of art – distinct, impactful, and tailor-made.As you step into the world of Omni Reach, you're not just accessing services; you're unlocking a realm of digital metamorphosis. Join hands with us to redefine your e-commerce trajectory. Let's soar to new heights together, harnessing the power of SAP Commerce Cloud, and scripting the future of digital success.Welcome to Omni Reach – where commerce meets its digital zenith.

Company details

Company typeScaleup

IndustryDigital Transformation Consulting

Company size51 - 200

Links

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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.
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