> Markdown version of [/jobs/ext/4634251-machine-learning-software-engineer](https://www.wearedevelopers.com/jobs/ext/4634251-machine-learning-software-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Machine Learning Software Engineer - **Company:** MORGAN & MORGAN, P.A. - **Location:** New York, NY, United States - **Experience:** Experienced - **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:** November 8, 2026 - **Apply:** https://www.juju.com/job/28_25303_8fc5be22f2005bd3a3fb69cc95d30366 ## 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, * 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