Software Engineer Trainee Jobs in Hackensack, NJ

This position is Onsite/Hybrid - Requires 3 days onsite, 2 days remote

Location: 150 E 42nd Street, New York, NY

Machine Learning Engineer III - AI Agent Engineer will oversee the design and development of sophisticated machine learning systems. They will collaborate closely with cross-functional teams to drive innovation and ensure the successful implementation of machine learning solutions.

Strength through Unity and Inclusion

The Mount Sinai Health System is committed to fostering an environment where everyone can contribute to excellence. We share a common dedication to delivering outstanding patient care. When you join us, you become part of Mount Sinai's unparalleled legacy of achievement, education, and innovation as we work together to transform healthcare. We encourage all team members to actively participate in creating a culture that ensures fair access to opportunities, promotes inclusive practices, and supports the success of every individual.

At Mount Sinai, our leaders are committed to fostering a workplace where all employees feel valued, respected, and empowered to grow. We strive to create an environment where collaboration, fairness, and continuous learning drive positive change, improving the well-being of our staff, patients, and organization. Our leaders are expected to challenge outdated practices, promote a culture of respect, and work toward meaningful improvements that enhance patient care and workplace experiences. We are dedicated to building a supportive and welcoming environment where everyone has the opportunity to thrive and advance professionally. Explore this opportunity and be part of the next chapter in our history.

About the Mount Sinai Health System:

Mount Sinai Health System is one of the largest academic medical systems in the New York metro area, with more than 48,000 employees working across eight hospitals, more than 400 outpatient practices, more than 300 labs, a school of nursing, and a leading school of medicine and graduate education. Mount Sinai advances health for all people, everywhere, by taking on the most complex health care challenges of our time - discovering and applying new scientific learning and knowledge; developing safer, more effective treatments; educating the next generation of medical leaders and innovators; and supporting local communities by delivering high-quality care to all who need it. Through the integration of its hospitals, labs, and schools, Mount Sinai offers comprehensive health care solutions from birth through geriatrics, leveraging innovative approaches such as artificial intelligence and informatics while keeping patients' medical and emotional needs at the center of all treatment. The Health System includes more than 9,000 primary and specialty care physicians; 13 joint-venture outpatient surgery centers throughout the five boroughs of New York City, Westchester, Long Island, and Florida; and more than 30 affiliated community health centers. We are consistently ranked by U.S. News & World Report's Best Hospitals, receiving high "Honor Roll" status, and are highly ranked: No. 1 in Geriatrics, top 5 in Cardiology/Heart Surgery, and top 20 in Diabetes/Endocrinology, Gastroenterology/GI Surgery, Neurology/Neurosurgery, Orthopedics, Pulmonology/Lung Surgery, Rehabilitation, and Urology. New York Eye and Ear Infirmary of Mount Sinai is ranked No. 12 in Ophthalmology. U.S. News & World Report's "Best Children's Hospitals" ranks Mount Sinai Kravis Children's Hospital among the country's best in several pediatric specialties. The Icahn School of Medicine at Mount Sinai is ranked No. 11 nationwide in National Institutes of Health funding and in the 99th percentile in research dollars per investigator according to the Association of American Medical Colleges. Newsweek's "The World's Best Smart Hospitals" ranks The Mount Sinai Hospital as No. 1 in New York and in the top five globally, and Mount Sinai Morningside in the top 20 globally.

Equal Opportunity Employer

The Mount Sinai Health System is an equal opportunity employer, complying with all applicable federal civil rights laws. We do not discriminate, exclude, or treat individuals differently based on race, color, national origin, age, religion, disability, sex, sexual orientation, gender, veteran status, or any other characteristic protected by law. We are deeply committed to fostering an environment where all faculty, staff, students, trainees, patients, visitors, and the communities we serve feel respected and supported. Our goal is to create a healthcare and learning institution that actively works to remove barriers, address challenges, and promote fairness in all aspects of our organization.

• Bachelor's degree in Computer Science, Data Science, or a related field.
• 4+ years of relevant experience in machine learning and back-end software development.
• 1+ years of hands-on experience building and deploying Generative AI, LLM, RAG, Copilot, or Agentic AI solutions in production environments.
• Experience with LLM platforms and frameworks such as Azure AI Foundry, Azure OpenAI, OpenAI, Anthropic, LangChain, LangGraph, Semantic Kernel, CrewAI, AutoGen, or similar technologies.
• Experience building RAG architectures utilizing vector databases such as Pinecone, Azure AI Search, Elasticsearch, Weaviate, Chroma, or equivalent platforms.
  Demonstrated end-to-end machine learning system development and operation experience, covering the complete Software Development Life Cycle (SDLC).
• Proficiency in multiple programming languages and machine learning frameworks and tools.
• Solid experience with both SQL and NoSQL databases.
• Extensive experience with Big Data technologies like Apache Spark.
• Hands-on experience in Unix environments.
• Practical knowledge and experience with at least one cloud system among AWS, Azure, or Google Cloud.
• Familiarity with continuous development and integration systems such as Jenkins, Git, Azure DevOps, and Terraform.
• A proven history in developing, deploying, and operating efficient and reliable machine learning systems.
• Strong leadership and effective communication skills to facilitate cross-functional collaboration throughout the organization.
• Experience in providing mentorship

Compensation Statement

The Mount Sinai Health System (MSHS) provides salary ranges that comply with the New York City Law on Salary Transparency in Job Advertisements. The salary range for the role is $132,000.00 - $198,065.00 Annually. Actual salaries depend on a variety of factors, including experience, education, and operational need. The salary range or contractual rate listed does not include bonuses/incentive, differential pay or other forms of compensation or benefits.

Non-Bargaining Unit, 271 - DTP Clinical Data Science - MSH, Mount Sinai Hospital

End-to-End System Responsibility:

• Assume full ownership of the design, development, deployment, governance, and continuous evolution of AI agent ecosystems and autonomous workflows.
• Architect and deliver end-to-end agentic AI solutions leveraging Large Language Models (LLMs), multi-agent systems, Retrieval-Augmented Generation (RAG), orchestration frameworks, and enterprise integrations.
• Lead the collaborative efforts with cross-functional teams, including data scientists and product managers, to ensure the successful deployment and robust maintenance of machine learning models.
• Oversee the continuous monitoring and timely updating of deployed models to guarantee enduring performance and reliability.
   

Technical Leadership:

• Exhibit technical leadership and mentorship to Machine Learning Engineer I, II, and other team members.
• Encourage knowledge exchange and promote professional growth within the team.
• Establish and enforce best practices for machine learning system development, including coding standards, code reviews, and comprehensive documentation.
• Serve as the primary contact for technical inquiries related to machine learning within the team, providing expert guidance and solutions.

AI Agent Design and Problem-Solving:

• Design, implement, and optimize intelligent agents capable of planning, reasoning, decision-making, workflow automation, and task execution.
• Develop agent frameworks that combine structured workflows, tool usage, knowledge retrieval, and autonomous decision-making.
• Solve complex technical and business challenges through innovative application of generative AI, machine learning, and software engineering principles.
• Drive root-cause analysis and resolution of agent performance issues, hallucinations, model drift, workflow failures, and integration challenges.
• Foster collaborative problem-solving across technical and business teams to deliver scalable AI-driven solutions.
   

Research and Development:

• Remain up-to-date with the latest advancements and trends in the fields of AI agents, Generative AI, software engineering and machine learning.
• Conduct proactive research to uncover new methods and techniques applicable to future projects.
• Lead initiatives to explore, test, and implement new technologies and frameworks, ensuring the team is always at the forefront of industry innovations.

Collaboration and Communication:

• Engage in effective communication and collaboration across various teams within the organization to ensure alignment and coordination in the execution of machine learning projects.
• Facilitate transparent and timely communication with all relevant stakeholders, ensuring that all are kept informed of project statuses, challenges, and achievements.
• Work collaboratively with cross-functional teams, fostering a cooperative environment for the seamless integration of machine learning systems into diverse organizational processes and workflows.
• Contribute to building strong interdepartmental relationships, enabling the efficient exchange of knowledge and expertise, and ensuring the successful realization of machine learning initiatives.

Additional Responsibilities:

• Develop and maintain project work plans, including critical tasks, milestones, timelines, interdependencies, and contingencies.  Tracks and reports progress.  Keeps stakeholders apprised of project status and implications for completion. 
• Prepare clear, well-organized project-specific documentation, including, at a minimum, analytic methods used, key decision points and caveats, with sufficient detail to support comprehension and replication. 
• Mentor other analysts on how to a) determine appropriate statistical analysis methods, b) leverage appropriate programing languages and tools, and c) generate and interpret statistical analysis outputs.
• Share development and process knowledge with other analysts in order to assure redundancy and continuously builds a core of analytical strength within the organization.
• Adheres to corporate standards for performance metrics, data collection, data integrity, query design, and reporting format to ensure high quality, meaningful analytic output.
• Works closely with IT on the ongoing improvement of Mount Sinai's integrated data warehouse, driven by strategic and business needs, and designed to ensure data and reporting consistency throughout the organization.
• Demonstrates advanced level proficiency with the principles and methodologies of process improvement. Applies these in the execution of responsibilities in support of a process focused approach.
• Other duties as assigned.