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Senior Machine Learning Jobs in New Jersey (NOW HIRING)

SageSure

Senior Machine Learning Engineer

Jersey City, NJ

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

SageSure

Senior Machine Learning Engineer

Jersey City, NJ · On-site

$127K - $168K/yr

As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with ...

Autodesk

$111K - $145K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Judge Group, Inc.

AI/ML Engineer

Jersey City, NJ · On-site

$70 - $80/hr

Senior Machine Learning Engineer / AI Engineer About the Role We are seeking a Senior Machine Learning Engineer to lead the design, development, and production deployment of advanced AI and machine ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

Instacart

As a Machine Learning Engineer, you will have the opportunity to collaborate closely with senior engineers and product leaders as part of your team. Together, you'll develop and enhance Instacart ...

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Senior Machine Learning information

What are some common challenges senior machine learning engineers face when deploying models to production, and how can they address them?

Senior Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining model performance over time, and integrating models seamlessly with existing systems. Addressing these requires robust monitoring frameworks, collaboration with data engineering and DevOps teams, and implementing strategies like continuous integration/continuous deployment (CI/CD) for ML. Proactive communication with stakeholders and staying updated on the latest MLOps tools can also help ensure smooth deployment and ongoing reliability.

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

To thrive as a Senior Machine Learning Engineer, you need a strong background in mathematics, statistics, computer science, and experience with designing and deploying machine learning models, typically supported by an advanced degree in a related field. Proficiency with programming languages such as Python or R, ML frameworks like TensorFlow or PyTorch, and experience with cloud platforms and version control systems are commonly required. Excellent problem-solving skills, communication abilities, and leadership in collaborating with cross-functional teams make candidates stand out. These skills ensure the effective development, scaling, and integration of ML solutions to drive business value and innovation.

What is a senior machine learning engineer?

Senior Machine Learning engineers are experienced professionals who design, develop, and deploy advanced machine learning models and systems. They typically lead projects, mentor junior team members, and collaborate with data scientists, software engineers, and stakeholders to solve complex problems using AI and data-driven techniques. Their responsibilities include researching new algorithms, optimizing model performance, and ensuring the scalability and reliability of machine learning solutions in production environments.
What are the most commonly searched types of Machine Learning jobs in New Jersey? The most popular types of Machine Learning jobs in New Jersey are:
What are popular job titles related to Senior Machine Learning jobs in New Jersey? For Senior Machine Learning jobs in New Jersey, the most frequently searched job titles are:
What job categories do people searching Senior Machine Learning jobs in New Jersey look for? The top searched job categories for Senior Machine Learning jobs in New Jersey are:
Senior Machine Learning jobs near you
Infographic showing various Senior Machine Learning job openings in New Jersey as of August 2026, with employment types broken down into 1% As Needed, 73% Full Time, 23% Part Time, 1% Temporary, and 2% Contract. Highlights an 87% Physical, 2% Hybrid, and 11% Remote job distribution.

Senior Machine Learning Engineer

SageSure

Jersey City, NJ

$127K - $168K/yr

Full-time

Re-posted 24 days ago

Job description

Overview: 

If you're looking for the stability of a profitable, growing company with the entrepreneurial spirit of a startup, we're hiring. SageSure, a leader in catastrophe-exposed property insurance, is seeking a Machine Learning Engineer.  As a Senior Machine Learning Engineer, you'll play a crucial role in optimizing orchestration processes and ensuring fast and efficient model deployment and delivery. You'll work closely with Software Engineers and Data scientists to streamline machine learning pipelines and implement best practices for managing and deploying ML models. 

What you'd be doing: 

  • Design and implement robust, scalable, and efficient data pipelines for training machine learning models. 
  • Develop prediction pipelines to ensure seamless integration of trained models into production environments. 
  • Create APIs and microservices to facilitate communication between machine learning models and other software modules. 
  • Design, build, and manage model deployment strategies to ensure reliability, scalability, and security in production environments. 
  • Implement monitoring and logging solutions to track model performance, data quality, and system health in real-time. 
  • Optimize orchestration processes to ensure efficient deployment and management of ML models. 
  • Implement cost-saving strategies to minimize infrastructure expenses while maximizing performance. 
  • Collaborate with cross-functional teams to identify bottlenecks and implement solutions to improve workflow efficiency. 

We're looking for someone who has: 

  • Bachelor's degree in Computer Science, Engineering, Mathematics, or a related technical field.  
  • 5-7 years of experience as an MLOps Engineer or similar role, with a proven track record of optimizing machine learning pipelines and infrastructure. 
  • Proficiency in cloud computing platforms (e.g., AWS, Azure, GCP) and containerization technologies (e.g., Docker, Kubernetes). 
  • Experience with orchestration tools and frameworks such as Airflow, Kubeflow, or MLflow. 
  • Experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-Learn. 
  • Experience in deploying machine learning models in production environments and managing model lifecycle. 
  • Excellent problem-solving skills and ability to work independently as well as part of a team. 
  • Strong communication skills and ability to collaborate effectively with cross-functional teams. 

Data at SageSure 

At SageSure, data isn't just a function-it's a force for innovation. Our Data organization brings together Data Science, Business Intelligence, and Data Management to power smarter decisions and deliver meaningful impact across the business. From predictive modeling to scalable data ecosystems and actionable insights, we turn complex information into clarity that drives real results. 

We're building a team of curious, collaborative problem-solvers who are passionate about using data to make a difference. Whether you're advancing machine learning capabilities, strengthening data governance, or uncovering insights that shape strategy, you'll play a critical role in defining how SageSure uses data to lead the future of insurance. 

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