ML Engineer focusing on building and operating large-scale machine learning systems at Autodesk. Collaborating with AI researchers and software engineers to create reliable ML infrastructure.
Responsibilities
Build and maintain components of ML pipelines for data preparation, model training, evaluation, deployment, and monitoring
Develop reliable software and infrastructure that supports scalable machine learning workflows
Contribute to distributed data processing and training systems used by researchers and engineering teams
Support data ingestion, transformation, validation, and serving for large-scale structured and semi-structured technical datasets
Improve automation, testing, CI/CD, observability, and operational reliability for ML systems
Troubleshoot data, infrastructure, and performance issues in collaboration with senior engineers
Participate in design discussions and contribute ideas that improve system scalability, maintainability, and efficiency
Document technical decisions, workflows, and operational processes clearly
Requirements
Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field, or equivalent industry experience
At least 2 years of industry experience in software engineering, machine learning infrastructure, distributed systems, data platforms, or related areas
Strong software engineering fundamentals, including coding, testing, debugging, and code quality
Proficiency in Python and experience building production-quality software
Experience with cloud platforms such as AWS, Azure, or GCP
Familiarity with containers, version control, CI/CD, and modern development workflows
Experience working with data-intensive systems, backend systems, or ML pipelines
Ability to work independently on well-defined problems with moderate ambiguity
ML Engineer training diffusion models for Hapiko’s voice - activated Stickerbox, which turns kids’ spoken ideas into stickers. Bringing Spin Master characters into production safely and on - model.
Trust & Safety ML Engineer safeguarding Hapiko’s generative - AI sticker printer for children. Owning moderation pipelines, safety evaluations, classifiers, red teaming, and compliance systems.
MLOps Engineer building production ML infrastructure, pipelines, and monitoring for exacare ai’s post - acute care AI platform. Scaling reliable systems that help healthcare teams make safer placement decisions.
Senior Data Engineer building cloud - native data and ML platforms for Hive.co’s event - marketing automation products. Owning pipelines, model infrastructure, and audience - data systems at scale.
Senior Machine Learning Engineer building causal and decision systems for CSC Generation’s AI - native omnichannel retail brands. Deploying machine learning that improves pricing and other commercial decisions.
Director leading agentic AI and machine learning products for Instacart’s grocery technology platform. Building retailer solutions and guiding teams from strategy through production deployment.
New - grad software engineer building Quora’s distributed ML platform, model serving, and developer tooling. Supporting Quora’s global knowledge - sharing product with scalable GPU infrastructure.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions for TD banking. Evaluating models, managing AI lifecycles, and supporting responsible implementation.
Applied Machine Learning Scientist developing Generative AI and predictive ML solutions at TD, a major North American bank. Supporting model evaluation, deployment, monitoring, and responsible AI governance.
Senior Machine Learning Engineer building conversational AI agents and production ML systems. Helping Numa automate automotive dealership service and sales through evaluation - first tooling and infrastructure.