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Software Engineer Ai Model Training Jobs in Paramus, NJ

Sr. Software Engineer (AI)

New York, NY · On-site

$134K - $176K/yr

As a Sr. Software Engineer (AI), you will sit at the intersection of deep technical capability and ... Model evaluation: Instrument and evaluate model outputs rigorously by defining evaluation ...

Senior Software Engineer - AI/ML

Manhattan, NY · On-site

$134K - $177K/yr

They are seeking a Senior Software Engineer - AI/ML to ship features across the backend stack ... g., training pipelines, experiment tracking, feature stores, model monitoring, evaluation ...

... models, MCP servers, agents, and agent skills/capabilities. As an SDE on this team, you will ... Training & Career Growth We're continuously raising our performance bar as we strive to become ...

... models, MCP servers, agents, and agent skills/capabilities. As an SDE on this team, you will ... Training & Career Growth We're continuously raising our performance bar as we strive to become ...

... models, MCP servers, agents, and agent skills/capabilities. As an SDE on this team, you will ... Training & Career Growth We're continuously raising our performance bar as we strive to become ...

Software Engineer - AI

New York, NY · On-site

$140K - $200K/yr

For this role, we value prior experience deploying or integrating AI models into real-world ... Training and professional development * Hybrid Work Schedule (4 days onsite, 3 if located > 1 hour ...

You won't be training LLMs or building foundation models from scratch. * You won't be focused on ... software engineering experience, with 2+ years working with LLMs or AI frameworks. * Strong ...

Senior Software Engineer, AI

New York, NY · On-site

$180K - $250K/yr

What This Role Is Not * ❌ You won't be training LLMs or building foundation models from scratch ... software engineering experience, with 2+ years working with LLMs or AI frameworks. * Strong ...

Deep understanding of modern AI and machine learning concepts, including large language models ... Strong understanding of software engineering best practices, including testing, observability ...

Deep understanding of modern AI and machine learning concepts, including large language models ... Strong understanding of software engineering best practices, including testing, observability ...

Software Engineer, AI Agents (Product-Minded LLM / Agentic Systems) Location: Remote (North America) Compensation: $180,000-$320,000 base (location-independent) + equity Contact / Apply: About Our ...

Showing results 41-60

Software Engineer Ai Model Training information

See Paramus, NJ salary details

$64.3K

$149.3K

$207.9K

How much do software engineer ai model training jobs pay per year?

As of Aug 20, 2026, the average yearly pay for software engineer ai model training in Paramus, NJ is $149,282.00, according to ZipRecruiter salary data. Most workers in this role earn between $121,400.00 and $175,100.00 per year, depending on experience, location, and employer.

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.

What cities near Paramus, NJ are hiring for Software Engineer Ai Model Training jobs?

Cities near Paramus, NJ with the most Software Engineer Ai Model Training job openings:

Principal Software Engineer - AI Foundations

J.P. Morgan

Jersey City, NJ • On-site

$140K - $188K/yr

Full-time

Medical, Retirement

Re-posted 3 days ago


Job description

hackajob is collaborating with J.P. Morgan to connect them with exceptional professionals for this role.

JOB DESCRIPTION

If you are looking for a game-changing career, working for one of the world's leading financial institutions, you've come to the right place.  

As a Principal Software Engineer at JPMorganChase within the Chief Data and Analytics Office (CDAO), you provide expertise and engineering excellence as an integral part of an agile team to enhance, build, and deliver trusted market-leading technology products in a secure, stable, and scalable way. Leverage your advanced technical capabilities and collaborate with colleagues across the organization to drive best-in-class outcomes across various technologies to support one or more of the firm's portfolios.  

Job Responsibilities  

  • Design, build, and troubleshoot AI-enabled applications and AI services, delivering creative, scalable solutions. 
  • Develop secure, high-quality production code; review, debug, and improve code written by others. 
  • Own and support SDK and service integrations, ensuring reliability, performance, and maintainability. 
  • Build and ship AI-powered features, including prompt design, function calling, and SDK/REST integrations (no prior experience required). 
  • Design and implement end-to-end MLOps capabilities including data/model versioning, reproducible training pipelines, CI/CD for models, deployment patterns, and continuous evaluation/monitoring. 
  • Contribute to next-generation training techniques (distributed fine-tuning, RLHF/DPO-style workflows, synthetic data generation, and automated evaluation) and productize them into reusable platform primitives. 
  • Identify recurring issues and automate remediation to improve reliability, resiliency, and operational performance of AI features and services. 
  • Create durable, reusable frameworks and platform components leveraged across teams, aligned to modern product development methodologies. 
  • Influence leaders and senior stakeholders across business, product, and technology to drive alignment and outcomes; foster a culture of diversity, opportunity, inclusion, and respect. 
  • Architects and governs agentic AI-enabled engineering workflows (using enterprise-authorized tools within the work environment) to improve delivery speed, code quality, and operational outcomes at scale (e.g., AI-driven PR review assistance, test generation/maintenance, release readiness checks, incident triage and root-cause acceleration), while defining guardrails for validation, security, resiliency, and reuse across teams. 
  • Applies knowledge of tools within the Software Development Life Cycle toolchain, including enterprise-authorized AI-assisted development and automation capabilities, to improve the value realized by automation at scale. 

Required qualifications, capabilities, and skills  

  • Formal training or certification on software engineering concepts and 7+ years applied experience  
  • Hands-on experience delivering system design, application development, testing, and operational stability for large-scale platforms and services. 
  • Expert proficiency in one or more programming languages (e.g., Python, Java, Scala, Go) with strong code quality, testing, and debugging practices. 
  • Demonstrated experience designing and leading adoption of agentic AI-enabled development practices (using enterprise-authorized tools within the work environment) across teams, including setting standards for human-in-the-loop validation, auditability/traceability of changes, and secure handling of sensitive data.  
  • Strong understanding of responsible AI use and control expectations in engineering workflows, including security/resiliency implications, data sensitivity, and risk-based governance; ability to influence senior technical leaders on safe scaling patterns and reuse.  
  • Proven ability to design and operate ML/LLM platforms: reproducible training pipelines, experiment tracking, model/data versioning, and continuous evaluation. 
  • Practical cloud-native experience (containers, orchestration, IaC, observability) and experience operating production systems with clear SLOs. 
  • Experience applying new methods to solve complex technology problems across one or more technical disciplines (platform engineering, ML systems, data engineering, distributed systems). 
  • Strong communication skills: able to present to and influence senior leaders/executives, translating complex technical topics into clear decisions and trade-offs. 
  • Strong understanding of business outcomes and product delivery, and ability to align platform roadmaps to measurable impact. 

Preferred qualifications, capabilities, and skills  

  • Practical experience with distributed compute and scalable model training/fine-tuning (e.g., Ray and/or comparable distributed frameworks), including performance, cost, and reliability trade-offs. 
  • Experience building model development platforms for LLMs/agentic systems (fine-tuning, evaluation harnesses, retrieval/tooling integration, prompt/agent testing). 
  • Experience with modern MLOps toolchains (CI/CD for models, model registries, feature/data stores, governance workflows) and production ML operations. 
  • Background in LLM evaluation, benchmarking, red-teaming, and quality measurement (offline + online), including experimentation and A/B testing. 
  • Experience designing multi-tenant platforms, reusable frameworks, and developer self-service capabilities at enterprise scale. 
  • Strong security-by-design experience for ML systems (secrets, access control, data handling, supply chain controls) and resiliency engineering. 

ABOUT US

JPMorganChase, one of the oldest financial institutions, offers innovative financial solutions to millions of consumers, small businesses and many of the world's most prominent corporate, institutional and government clients under the J.P. Morgan and Chase brands. Our history spans over 200 years and today we are a leader in investment banking, consumer and small business banking, commercial banking, financial transaction processing and asset management.

We offer a competitive total rewards package including base salary determined based on the role, experience, skill set and location. Those in eligible roles may receive commission-based pay and/or discretionary incentive compensation, paid in the form of cash and/or forfeitable equity, awarded in recognition of individual achievements and contributions. We also offer a range of benefits and programs to meet employee needs, based on eligibility. These benefits include comprehensive health care coverage, on-site health and wellness centers, a retirement savings plan, backup childcare, tuition reimbursement, mental health support, financial coaching and more. Additional details about total compensation and benefits will be provided during the hiring process. 

We recognize that our people are our strength and the diverse talents they bring to our global workforce are directly linked to our success. We are an equal opportunity employer and place a high value on diversity and inclusion at our company. We do not discriminate on the basis of any protected attribute, including race, religion, color, national origin, gender, sexual orientation, gender identity, gender expression, age, marital or veteran status, pregnancy or disability, or any other basis protected under applicable law. We also make reasonable accommodations for applicants' and employees' religious practices and beliefs, as well as mental health or physical disability needs. Visit our FAQs for more information about requesting an accommodation.

JPMorgan Chase & Co. is an Equal Opportunity Employer, including Disability/Veterans

ABOUT THE TEAM

Our professionals in our Corporate Functions cover a diverse range of areas from finance and risk to human resources and marketing. Our corporate teams are an essential part of our company, ensuring that we're setting our businesses, clients, customers and employees up for success.