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Python Ml Developer Jobs in Fort Lee, NJ (NOW HIRING)

Winaxis

Lead Python Developer

New York, NY · On-site

$153K - $188K/yr

Lead Python Developer - Lead the design, development, and deployment of enterprise-grade ... ML models for advanced business insights. - Ensure solutions comply with security best practices ...

Photon

Python + Gen AI Developer - New York

Manhattan, NY · On-site

$55 - $76/hr

Python, FastAPI, and Asynchronous Programming. RAG & Data: PostgreSQL, Vector Databases, and ... ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management ...

Photon

Python + Gen AI Developer - New York

Manhattan, NY · On-site

$55 - $76/hr

Python, FastAPI, and Asynchronous Programming. RAG & Data: PostgreSQL, Vector Databases, and ... ML/DL: PyTorch, TensorFlow, and Model Fine-tuning. Deployment: Docker, Production API management ...

iTech US, Inc.

AI/ML Engineer (MLops)

Woodbridge, NJ · On-site

AI/ML Engineer (MLOps) Iselin, NJ 12 months Technical Expertise ML/Al Frameworks: PyTorch ... Python, C/C++, Java, SQL, Scala, GoLang, JavaScript Cloud & Infra: AWS (SageMaker, S3, Lambda ...

Soni Resources

Senior AI/ML Engineer

New York, NY · On-site

$210K/yr

Write scalable, maintainable, and high-quality Python code for AI and ML applications * Optimize ... Advanced Python programming skills focused on AI/ML engineering and LLM application development

MLabs

Senior ML Engineer

New York, NY · On-site

$300K - $375K/yr

Develop and maintain production Python systems for data collection, enrichment, feature extraction ... Full-Stack ML Engineering Capability: Strong software engineering and data pipeline fundamentals to ...

MLabs

Senior ML Engineer

New York, NY · On-site

$300K - $375K/yr

Develop and maintain production Python systems for data collection, enrichment, feature extraction ... Full-Stack ML Engineering Capability: Strong software engineering and data pipeline fundamentals to ...

MLabs Ltd

Senior ML Engineer

Manhattan, NY · On-site

$300 - $375/hr

Develop and maintain production Python systems for data collection, enrichment, feature extraction ... Full-Stack ML Engineering Capability: Strong software engineering and data pipeline fundamentals to ...

Starr

AI/ML Engineer

Manhattan, NY · On-site

The AI/ML Engineer will uncover meaningful data patterns and transform them into actionable ... Python analytics experience with a proven track record in advanced analytics as well as hands-on ...

Appgate

Staff Machine Learning Engineer

Manhattan, NY · On-site

$180K - $220K/yr

Expertise in Python , ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn), and CI/CD (GitHub ... AI / Fraud Prevention Engineering Experience: 5+ years (Staff) or 8+ years (Principal) in ML or ...

Soni Resources

AI/ML Engineer

New York, NY · On-site

$175K/yr

We are seeking an AI/ML Engineer to help develop and deploy machine learning solutions that ... experience in Python or R * Experience working with both structured and unstructured data ...

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All JobsPython Ml Developer JobsPython Ml Developer Jobs in Fort Lee, NJ

Python Ml Developer information

See Fort Lee, NJ salary details

$13

$61

$90

How much do python ml developer jobs pay per hour?

As of Aug 12, 2026, the average hourly pay for python ml developer in Fort Lee, NJ is $61.18, according to ZipRecruiter salary data. Most workers in this role earn between $50.43 and $69.52 per hour, depending on experience, location, and employer.

What does a Python ML Developer do?

A Python ML Developer designs, builds, and deploys machine learning models using the Python programming language. They work with large datasets, clean and process data, select appropriate algorithms, and use libraries like TensorFlow, PyTorch, or scikit-learn to implement solutions. Their work often involves collaborating with data scientists and engineers to integrate machine learning models into applications. Additionally, they may be responsible for testing, tuning, and optimizing models to achieve the best possible performance in real-world scenarios.

What are some common challenges Python ML Developers face when deploying machine learning models to production?

Python ML Developers often encounter challenges such as ensuring model scalability, managing dependencies, and maintaining reproducibility when deploying models into production environments. Integrating machine learning models with existing systems can require close collaboration with DevOps and software engineering teams to streamline workflows and automate deployment pipelines. Additionally, monitoring model performance over time and handling data drift are crucial responsibilities to ensure continued accuracy and reliability of deployed solutions.

What are the key skills and qualifications needed to thrive as a Python ML Developer?

To thrive as a Python ML Developer, you need strong programming skills in Python, a solid understanding of machine learning algorithms, and a background in mathematics or statistics, often supported by a degree in computer science, engineering, or a related field. Familiarity with tools and libraries such as TensorFlow, scikit-learn, PyTorch, and version control systems like Git is essential, along with experience using data visualization and cloud platforms. Critical soft skills include problem-solving, adaptability, and effective communication to collaborate with cross-functional teams and explain complex models to stakeholders. These skills ensure the successful development, deployment, and maintenance of machine learning solutions that drive business value.

What is the difference between Python Ml Developer vs Data Scientist?

AspectPython Ml DeveloperData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; Python, ML certificationsBachelor's/Master's in Data Science, Statistics, or related; Python, ML certifications
Work EnvironmentSoftware development teams, AI/ML projectsResearch, data analysis, modeling teams
Employer & Industry UsageTech companies, startups, AI firmsFinance, healthcare, tech, research institutions
Common Search & ComparisonYesYes

Python ML Developers focus on building and deploying machine learning models using Python, often working closely with software engineering teams. Data Scientists analyze data, create models, and generate insights, often using Python along with statistical tools. While both roles require Python and ML knowledge, Python ML Developers are more involved in implementation and deployment, whereas Data Scientists focus on data analysis and research.

What cities near Fort Lee, NJ are hiring for Python Ml Developer jobs? Cities near Fort Lee, NJ with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Fort Lee, NJ as of July 2026, with employment types broken down into 83% Full Time, 3% Part Time, 1% Temporary, and 13% Contract. Highlights an 81% Physical, 4% Hybrid, and 15% Remote job distribution, with an average salary of $127,264 per year, or $61.2 per hour.

ML Platform Engineer

Infinity Tech Group Inc

Manhattan, NY • On-site

Other

Posted 29 days ago

Job description

Role Overview

This role will help enable algorithm development, model packaging, model registration, reproducible execution, and governed deployment workflows across imaging datasets, Integrated Data Products, and Analysis-Ready Datasets.

The role is focused on ML platform engineering, MLOps, model integration, and validation readiness rather than developing new clinical interpretation algorithms.

Key Responsibilities
  • Build and support ML / MLOps capabilities within the Global Imaging Platform.
  • Integrate ML models and workflows with GIP IDPs, ARDs, App Catalog, and model registry.
  • Support SageMaker integration as the first connected algorithm development environment.
  • Package algorithms for repeatable execution, versioning, lineage, and auditability.
  • Implement model metadata, version control, experiment tracking, and reproducible build patterns.
  • Support in-platform inferencing workflows for SageMaker-hosted or connected models.
  • Work with data engineers, architects, and validation teams to ensure traceability from dataset to model output.
  • Support CI/CD pipelines for ML model packaging, deployment, rollback, and promotion.
  • Contribute to governance, observability, monitoring, and lifecycle controls for ML models.
  • Support validation evidence generation, including documentation for GxP-ready workflows where applicable.
  • Collaborate with architects, data scientists, platform engineers, and Genentech SMEs to align ML workflows with platform standards.
  • Assist with onboarding future connected environments such as Vertex AI, Posit Workbench, and HPC.
Required Skills
  • Strong hands-on experience with Python and ML engineering libraries.
  • Experience with AWS SageMaker, model deployment, and endpoint / inference workflows.
  • Experience with MLOps, model registry, experiment tracking, model versioning, and reproducibility.
  • Familiarity with tools such as MLflow, Docker, GitHub, CI/CD pipelines, Kubernetes / EKS, or similar.
  • Experience working with data pipelines, APIs, metadata, and lineage concepts.
  • Understanding of model packaging, release management, rollback, and environment reproducibility.
  • Ability to work with cross-functional teams across architecture, data engineering, validation, and product teams.
  • Strong documentation skills for technical designs, implementation notes, and validation evidence.
Preferred Skills
  • Experience in life sciences, clinical imaging, healthcare AI, or regulated data platforms.
  • Familiarity with imaging formats and workflows such as DICOM, radiology, ophthalmology, or digital pathology.
  • Experience with PyTorch, TensorFlow, or similar ML frameworks.
  • Exposure to GxP, SaMD, validation, audit trail, traceability, or 21 CFR Part 11-aligned environments.
  • Experience integrating ML models into enterprise platforms or application catalogs.
  • Experience with cloud-native architecture and observability dashboards.
Expected Deliverables
  • ML model packaging and registration workflows.
  • SageMaker integration support for GIP algorithm framework.
  • Reproducible ML execution patterns.
  • Model metadata, lineage, and versioning implementation.
  • ML lifecycle documentation and technical implementation notes.
  • Support for validation evidence and audit-readiness documentation.
  • Support for model deployment, monitoring, and rollback workflows.
Qualifications
  • Bachelor s or Master s degree in Computer Science, Data Science, Engineering, Biomedical Engineering, or related field.
  • 6+ years of experience in ML engineering, MLOps, or applied AI platform development.
  • Prior experience supporting enterprise-scale ML platforms or regulated data environments is preferred.

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