Location:

Jersey City ,

NJ Duration:

Contract to

Hire Role/Title:

ML Engineer ## Key Responsibilities

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. ## Required Qualifications
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.

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