> Markdown version of [/jobs/ext/1473068-ml-engineer](https://www.wearedevelopers.com/jobs/ext/1473068-ml-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # ML engineer - **Company:** Whiz Global LLC - **Location:** Jersey City, NJ, United States - **Experience:** Expert - **Contract:** Temporary to permanent - **Skills:** Java (Programming Language), Artificial Intelligence, Amazon Web Services, Computer Vision, Big Data, Program Optimization, Software Quality, Code Review, Computer Programming, Continuous Integration, Data Structures, Distributed Computing Environment, Distributed Systems, Python (Programming Language), Machine Learning, Natural Language Processing, Performance Tuning, Tensorflow, Software Engineering, User-Centered Design, Pytorch, Large Language Models, Deep Learning, Containerization, Scikit Learn, Kubernetes, Information Technology, Machine Learning Operations, Data Pipelines, Docker - **Published:** July 28, 2026 - **Apply:** https://www.dice.com/job-detail/041e52f9-8cff-4c5b-816c-c00ba27aacec ## About the Role Bachelor''s or Master''s degree in Computer Science, Data Science, Engineering, or a related field. - **10+ years** of hands-on experience deploying machine learning models in production, with a track record of delivering large-scale systems. - Expert-level programming skills in **Python**, with basic understanding in additional languages such as Java, Scala. - Advanced understanding of data structures, algorithms, distributed systems, and software engineering principles. - Extensive experience with cloud platforms (AWS) and containerization/orchestration (Docker, Kubernetes). Deep experience with MLOps tooling (MLflow, Kubeflow, SageMaker, Vertex AI) and CI/CD for ML. - Proven experience designing and maintaining large-scale data processing systems. - Demonstrated experience leading technical projects and mentoring engineers. ## Preferred Qualifications -- Advanced knowledge of deep learning, NLP, computer vision, or large language models. - Experience with distributed training, model optimization, and high-throughput serving infrastructure. - Understanding of ML frameworks such as **TensorFlow, PyTorch, or scikit-learn**. ## Core Competencies - Strategic thinking with strong analytical and problem-solving capabilities. - Exceptional communication skills, with the ability to influence both technical and non-technical stakeholders. - Proven technical leadership and mentorship abilities. - Ability to navigate ambiguity, drive initiatives independently, and manage competing priorities. - Strong ownership mindset and commitment to engineering excellence. ## Description Lead the end-to-end design, development, and deployment of scalable machine learning models and systems in production. - Architect robust, high-performance ML infrastructure and data pipelines that support training, validation, and real-time inference. - Drive technical decision-making, setting standards for code quality, model governance, and MLOps practices. - Mentor and provide technical guidance to junior and mid-level engineers through code reviews, pairing, and knowledge sharing. - Partner with data scientists to operationalize advanced research into reliable, production-ready services. - Define and implement monitoring, observability, and automated retraining strategies to ensure model reliability and detect drift. - Collaborate with product, engineering, and business leadership to shape ML roadmaps and translate strategic goals into technical deliverables. - Evaluate and introduce emerging ML technologies, frameworks, and methodologies to keep the organization at the forefront of innovation. - Own the technical health of ML systems, including performance optimization, cost efficiency, and scalability. ## Related Videos - [Alibaba Big Data and Machine Learning Technology](https://www.wearedevelopers.com/videos/37-alibaba-big-data-and-machine-learning-technology) - [The state of MLOps - machine learning in production at enterprise scale](https://www.wearedevelopers.com/videos/369-the-state-of-mlops-machine-learning-in-production-at-enterprise-scale) - [Docker Compose: Rediscovered](https://www.wearedevelopers.com/videos/1978-docker-compose-rediscovered) - [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding) - [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops) - [Docker build without Docker](https://www.wearedevelopers.com/videos/100114-docker-build-without-docker) ## Related Articles - [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models) - [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it) - [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production) - [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer) - [MLOps And AI Driven Development](https://www.wearedevelopers.com/magazine/82-mlops-and-ai-driven-development) - [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)