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# Machine Learning Software Engineer

- **Company:** Morgan & Morgan
- **Location:** New York, United States
- **Experience:** Experienced
- **Salary:** $220,000.0
- **Contract:** Permanent contract
- **Skills:** Testing (Software), Agile Methodology, Artificial Intelligence, Amazon Web Services, Applications Architecture, Cloud Computing, Cloud Engineering, Software Quality, Code Review, Continuous Integration, Fault Tolerance, Python (Programming Language), Machine Learning, Open Source Technology, Scrum Methodology, Software Engineering, Datadog, Test-Driven Development (TDD), ReactJS, Large Language Models, Backend, Fastapi, Machine Learning Operations, Front End Software Development, Terraform
- **Published:** September 13, 2026
- **Apply:** https://www.dice.com/job-detail/76f4daaa-2e3c-4bc8-ab86-df959f73dc29

## About the Role

We're looking for a Machine Learning Software Engineer who is passionate about building high-quality software and leading engineering teams with a strong sense of technical rigor and collaboration. In this role, you'll drive technical direction, mentor engineers, and guide the team toward sound engineering practices in a fast-paced, agile environment.

This is a hands-on leadership role, balancing deep technical contributions with thoughtful leadership and mentorship., 7+ years of professional software development experience
4+ years of professional experience with AI/ML/LLM or exposure to machine learning systems and large language models
Deep proficiency in Python, particularly with FastAPI or similar frameworks
Strong experience with React and front-end application architecture
Production experience with AWS and modern cloud-native architectures
Demonstrated expertise in software testing, quality assurance, and CI/CD pipelines
Experience with Agile development methodologies and leading agile ceremonies
Strong communicator and collaborator; able to lead design reviews and drive consensus
Proven track record of mentoring and elevating teammates' technical growth
Exceptional communication and collaboration skills with a focus on cross-functional alignment

Nice to Have:
Experience with infrastructure-as-code (Terraform, CDK, or similar)
Familiarity with system observability tools (e.g., Datadog, OpenTelemetry)
Contributions to open source or technical writing (blogs, documentation, etc.)

## Description

Design, build, and deploy ML models and pipelines at scale
Partner with software engineers to integrate ML into products
Elevate code quality: Champion test-driven development, code hygiene, and clean architecture across the team
Design leadership: Own the authoring and review of technical design documents that drive shared understanding and decision-making across teams
Agile delivery: Lead sprint planning, retrospectives, and incremental delivery with a strong bias toward iteration and value delivery
Lead by example: Design and implement scalable, robust systems across the backend (Python/FastAPI), frontend (React), and cloud infrastructure (AWS)
Raise the bar: Set and uphold high standards for code quality, testing, performance, and maintainability
Mentor and grow engineers: Provide technical mentorship and encourage a growth mindset through regular feedback and coaching
Drive technical alignment: Lead code reviews, design reviews, and engineering discussions that result in thoughtful, well-documented decisions
Champion documentation: Author and review technical design documents to guide team implementation and maintain long-term clarity
Build for resilience: Design systems with fault tolerance, observability, and graceful degradation in mind; guide the team in applying principles of reliability and operational excellence
Lead incident response and learning: Participate in and improve incident response processes, drive actionable postmortems, and promote a culture of continuous improvement
Cross-functional alignment: Collaborate with product managers, designers, and other stakeholders to ensure alignment on roadmap priorities and delivery timelines


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