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Python Ml Developer Jobs in Cranford, NJ (NOW HIRING)

Mondo

Sr. ML Engineer / ML Architect

Manhattan, NY

$90 - $110/hr

Job Title: Sr. ML Engineer / ML Architect Location-Type: Remote Start Date Is: June 16 Duration ... Python-heavy environment * Some Java exposure preferred (Kafka ecosystem dependencies) * Snowflake ...

AceStack LLC

AI/ML Engineer

Lebanon, NJ

Programming experience in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) * Experience with version control systems (Git) and automation tools * Understanding of data engineering ...

IT America Inc

Lead Python Developer

New York, NY · Remote

$143.30K - $176.10K/yr

Lead Python Developer (Expert Level) Location: Remote (But need consultant from EST time zone ... AI/ML, don't have to be expert with this but it is required to have some decent experience as this ...

Harnham

Principal ML Engineer

Manhattan, NY

Drive best practices in Python engineering , testing, and CI/CD * Partner with leadership on AI strategy, tooling, and platform direction What You Bring * 10+ years of experience in ML Engineering ...

Equiliem

ML Engineer

Morristown, NJ

ML Engineer - AI Operations Location: Morristown, NJ (100% Onsite from Day 1) Duration: 6 Months ... Strong experience with Python, SQL, Git/GitLab * Hands-on expertise with MLflow, Snowflake, Power ...

Samprasoft

Machine Learning Engineer

Jersey City, NJ

Experience in Object Oriented Programming (Java, Scala, Python), SQL, Unix scripting or related programming languages and exposure to some of Python's ML ecosystem (numpy, panda, sklearn, tensorflow ...

Argyle Infotech

Gen AI ML Engineer

Manhattan, NY

Strong proficiency in programming languages such as Machine Learning Algorithms, Python, Hadoop ... If you are a skilled and innovative ML Engineer with a passion for Generative AI, and have a desire ...

Nexstar Media Group, Inc.

AI/ML Engineer

Manhattan, NY · On-site

Required : • Bachelor's degree required. • 2 - 5 years of hands-on ML engineering experience in a professional setting • Strong Python proficiency with production-quality coding standards • ...

eTeam

AI/ML Engineer - Generative AI

Manhattan, NY

AI/ML Engineer - Generative AI Location: New York, NY 10004 (Onsite. LOCAL CANDIDATES ONLY ... Proficiency in technologies like Agentic AI, Gen AI, RAG, Python, Lang Graph, Lang Chain * Design ...

ShiftCode Analytics

AI/ML Engineer

Brooklyn, NY · Hybrid

Proficient in Python programming, with hands-on experience using AI/ML frameworks such as TensorFlow, PyTorch, or similar. * Hands-on experience with MLOps, including model training, validation ...

ShiftCode Analytics

AI/ML Engineer

Manhattan, NY · Hybrid

Proficient in Python programming, with hands-on experience using AI/ML frameworks such as TensorFlow, PyTorch, or similar. * Hands-on experience with MLOps, including model training, validation ...

SoHo Dragon

Senior AI/ML Engineer

Manhattan, NY · On-site

$115K - $157.90K/yr

Senior AI/ML Engineer Client: Global advertising company Location: Chicago or NYC; 3 days a week ... Strong programming skills in languages such as Python, SQL/NoSQL etc. * Build analytical approach ...

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How much do python ml developer jobs pay per hour?

As of Jun 1, 2026, the average hourly pay for python ml developer in Cranford, NJ is $59.73, according to ZipRecruiter salary data. Most workers in this role earn between $49.23 and $67.84 per hour, depending on experience, location, and employer.

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

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 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 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 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 Cranford, NJ are hiring for Python Ml Developer jobs? Cities near Cranford, NJ with the most Python Ml Developer job openings:
Python Ml Developer jobs near you
Infographic showing various Python Ml Developer job openings in Cranford, NJ as of May 2026, with employment types broken down into 1% Internship, 80% Full Time, 14% Part Time, 3% Temporary, and 2% Contract. Highlights an 76% Physical, 5% Hybrid, and 19% Remote job distribution, with an average salary of $124,237 per year, or $59.7 per hour.
Sr. ML Engineer / ML Architect

Sr. ML Engineer / ML Architect

Mondo

Manhattan, NY

$90 - $110/hr

Contractor

Medical, Dental, Vision, Retirement

Posted 4 days ago

Job description

Job Title: Sr. ML Engineer / ML Architect
Location-Type: Remote
Start Date Is: June 16
Duration: (contract, perm, etc) 12 Month Contract
Compensation Range: $90 - 110$/hr W2
Benefits: Eligible for Health, Dental, Vision, 401K
Must be authorized to work in the U.S. This position is not eligible for sponsorship .
Job Description:

Our client is hiring a senior-level ML Engineer / ML Architect to help redesign and productize a highly business-critical internal system that supports sales account assignment and book-of-business management across 1,000 sales reps.

The current system:

  • Handles extremely complex business logic and rule orchestration
  • Requires intensive compute and optimization processing
  • Has very little room for error due to direct downstream business impact
  • Creates operational escalations quickly when issues occur
  • Is currently owned heavily by one long-tenured math PhD engineer who needs to roll off the project after several years of ownership
The team wants to:
  • Build a more scalable and configurable data product
  • Improve optimization performance and compute efficiency
  • Productize internal tooling for business users
  • Create real-time simulation/testing capabilities for sales operations users
  • Improve feature store architecture and pipeline design
  • Reduce infrastructure/storage bottlenecks and solver performance issues

Core Responsibilities

  • Architect and optimize a large-scale internal data product supporting sales operations
  • Design scalable feature store infrastructure
  • Build and optimize ML/data pipelines
  • Improve solver performance and optimization efficiency
  • Design configurable systems for business users to run real-time simulations/mock runs
  • Help define and architect pipeline orchestration and system sequencing
  • Partner with existing software engineers and ML engineers on implementation
  • Improve compute efficiency and storage optimization
  • Build feedback loops between optimization systems and end-user configuration tooling
  • Help productize internal operational systems into more robust platforms

Technical Environment:

  • Python-heavy environment
  • Some Java exposure preferred (Kafka ecosystem dependencies)
  • Snowflake/data warehouse environment
  • Kubernetes deployment infrastructure
  • Large-scale AWS infrastructure
  • Constraint programming / optimization solver systems
  • Heavy linear algebra and operations research concepts

Technical Must-Haves:

  • Strong Python engineering background
  • Experience building large-scale data infrastructure and pipelines
  • Experience designing scalable backend/data systems
  • Strong systems architecture mindset
  • Experience optimizing compute-heavy systems
  • Exposure to optimization research / operations research / constraint programming
  • Experience working with solver-based systems or large optimization problems
  • Strong understanding of feature engineering and feature store architecture
  • Experience with web services and production infrastructure
  • Ability to think through data modeling and pipeline architecture
  • Strong performance optimization mindset

Soft Skills:

  • Strong problem-solving ability
  • Systems thinking
  • Ability to architect ambiguous solutions
  • Comfortable operating in highly complex environments
  • Strong communication around technical tradeoffs
  • Strategic mindset beyond pure implementation
  • Ability to collaborate closely with existing engineering teams