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Contract Machine Learning Software Engineer Jobs in New Jersey

The Software Engineer contributes to the development of analytics solutions, supports the ... AI & Machine Learning: LLM integration, prompt engineering, embeddings, model evaluation ...

Job Title: Quantitative Software Engineer About Us Edgestream Partners is a team of scientists ... Experience building resilient, parallelized data transformation architectures for machine learning ...

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

$139K - $168K/yr

At Poe, we use Machine Learning in various parts of the product - bot routing, agent flow, code ... Previous software engineering experience via an internship, work experience, or coding competition

Showing results 41-60

Contract Machine Learning Software Engineer information

How does a contract machine learning software engineer typically collaborate with full-time team members during a project?

As a Contract Machine Learning Software Engineer, you will often work closely with full-time data scientists, software engineers, and product managers. Collaboration usually happens through regular stand-up meetings, code reviews, and shared documentation platforms. Despite being a contractor, you’re expected to integrate seamlessly with the team, communicate progress transparently, and adapt to the company’s workflows. Building strong relationships and proactively seeking feedback can help ensure your contributions align with the project’s goals and timelines.

What is the difference between Contract Machine Learning Software Engineer vs Data Scientist?

AspectContract Machine Learning Software EngineerData Scientist
CredentialsBachelor's or Master’s in CS, ML, or related fields; experience with ML frameworksBachelor's or Master’s in Statistics, Data Science, or related fields; strong analytical skills
Work EnvironmentProject-based, often remote, focused on developing ML models and softwareData analysis, visualization, and interpretation, often in research or business settings
Employer & Industry UsageTech companies, startups, consulting firms; used for deploying ML solutionsResearch institutions, finance, healthcare, and tech; used for insights and decision-making

The main difference is that Contract Machine Learning Software Engineers focus on developing and deploying ML models as software solutions, while Data Scientists analyze data to generate insights. Both roles require strong technical skills, but their primary objectives and work environments differ.

What are the key skills and qualifications needed to thrive as a contract machine learning software engineer?

To thrive as a Contract Machine Learning Software Engineer, you need a strong background in computer science, proficiency in programming languages like Python, and expertise in machine learning algorithms, typically supported by a relevant degree or equivalent experience. Familiarity with frameworks and tools such as TensorFlow, PyTorch, scikit-learn, and cloud platforms, along with knowledge of version control systems like Git, is essential. Strong problem-solving abilities, communication skills, and the ability to work independently or with cross-functional teams make someone stand out in this role. These skills ensure efficient delivery of scalable machine learning solutions that meet client requirements and project timelines.

What is a contract machine learning software engineer?

A Contract Machine Learning Software Engineer is a professional who is hired on a temporary or project basis to design, develop, and deploy machine learning models and systems. They often work with organizations that need specialized expertise for a limited duration, helping to build algorithms, analyze data, and integrate AI solutions into existing software products. Contract engineers typically have strong backgrounds in programming, mathematics, and data science, and they may work remotely or on-site. Their responsibilities can range from data preprocessing and model training to deploying models in production environments. This arrangement allows companies to access advanced machine learning skills without committing to a full-time hire.

What are the most commonly searched types of Machine Learning Software Engineer jobs in New Jersey?

The most popular types of Machine Learning Software Engineer jobs in New Jersey are:

What are popular job titles related to Contract Machine Learning Software Engineer jobs in New Jersey?

For Contract Machine Learning Software Engineer jobs in New Jersey, the most frequently searched job titles are:

What job categories do people searching Contract Machine Learning Software Engineer jobs in New Jersey look for?

The top searched job categories for Contract Machine Learning Software Engineer jobs in New Jersey are:

What cities in New Jersey are hiring for Contract Machine Learning Software Engineer jobs?

Cities in New Jersey with the most Contract Machine Learning Software Engineer job openings:

Lead Machine Learning Engineer (Locals to NJ preferred) - W2 Role

Saransh Inc

Weehawken, NJ • On-site

$111K - $146K/yr

Contractor

Re-posted just now


Job description

Role: Lead / Senior Machine Learning Enginee
Location: Weehawken, NJ (Day 1 Onsite) - Locals preferred
Job Type: W2 Contract
 
Position Overview:
  • We are seeking a highly skilled and experienced Lead/ Senior Machine Learning Engineer with expertise in Python and hands-on experience designing innovative solutions using Agentic systems and modeling large language models (LLMs).
  • The ideal candidate will hold an Azure Certified AI Practitioner certification and demonstrate deep knowledge of Azure’s AI services and data engineering tools.
 
Key Responsibilities:
AI and Agentic Solutions Development:
  • Design, develop, and implement agentic systems for real-time decision-making processes.
  • Integrate multimodal AI agents capable of proactive problem-solving using machine learning and automation.
  • Collaborate with stakeholders to architect solutions that align with organizational goals.
LLM Development and Optimization:
  • Build, customize, and fine-tune large language models (LLMs) for diverse business applications.
  • Research and experiment with LLM architectures to optimize performance for specific use cases like NLP, conversational AI, and summarization.
  • Deploy LLMs efficiently on Azure services such as Azure Machine Learning, OpenAI Service, and Cognitive Services.
Data Engineering Expertise:
  • Architect and maintain complex data pipelines and frameworks on Azure.
  • Work with relational and non-relational databases to preprocess and manage datasets for AI models.
  • Leverage Azure tools like Data Factory, Synapse Analytics, and Databricks for ETL processes and advanced analytics workflows.
Python Development and Software Engineering:
  • Write high-quality, scalable Python code for machine learning and data engineering applications.
  • Develop reusable libraries for AI models and data processing workflows.
  • Collaborate with DevOps teams to ensure robust CI/CD pipelines and deploy production-ready solutions in cloud environments.
Collaboration and Leadership:
  • Mentor and guide junior engineers on best practices in data engineering and machine learning.
  • Collaborate with cross-functional teams, including data scientists, product managers, and business analysts.
  • Proactively contribute to strategic roadmaps for AI-powered business solutions.
Required Qualifications:
  • Azure Certified AI Practitioner (or equivalent Azure certification in AI and data engineering).
  • Demonstrable expertise in Python, with advanced knowledge of libraries such as Pandas, NumPy, PyTorch, TensorFlow, and LangChain.
  • Extensive experience designing and building Agentic solutions (e.g., autonomous agents capable of advanced decision-making and orchestration).
  • Hands-on experience with modeling and deploying LLMs (fine-tuning, prompt engineering, optimization).
  • Proficiency with Microsoft Azure ecosystem, including services like Azure Machine Learning, OpenAI Service, Cognitive Services, and Databricks.
  • Strong understanding of machine learning, natural language processing (NLP), and generative AI concepts.
  • Familiarity with best practices in data engineering, such as data modeling, schema design, ETL processes, and pipeline optimization.
Preferred Qualifications:
  • Advanced degree (Master’s or PhD) in Computer Science, Data Engineering, AI/ML, or a related field.
  • Experience with integrating LLMs into production environments for real-world applications (e.g., chatbots, document summarization, generative design).
  • Knowledge of distributed computing frameworks (e.g., Spark, Hadoop).
  • Familiarity with versioning tools (e.g., Git), containerization (e.g., Docker), and orchestration (e.g., Kubernetes).