Machine Learning Engineer – Pre-IPO Tech CompanyAbout The RoleWe are looking for a highly skilled Machine Learning Engineer to help design, build, and scale ML-driven systems at a $500M pre-IPO technology company. Our mission is to harness machine learning and AI to deliver intelligent, data-powered products to customers at global scale.In this role, you will work at the intersection of applied research and engineering. You’ll build training and inference pipelines, optimize models for performance in production, and collaborate with product and data teams to turn cutting-edge algorithms into customer-facing features. This is a hands-on opportunity to shape the future of AI-driven products at a high-growth company on the path to IPO.What You’ll Do
Model Development: Collaborate with data scientists and researchers to prototype, train, and evaluate machine learning models for real-world applications.
Productionize ML: Build and optimize pipelines for training, deployment, monitoring, and scaling models in production environments.
Infrastructure & Tools: Design ML infrastructure leveraging cloud platforms, GPUs, and distributed systems for large-scale learning and inference.
Experimentation: Run large-scale experiments (A/B testing, online learning) to measure model impact and refine algorithms.
Data Collaboration: Partner with data engineers to ensure robust, clean, and high-quality datasets for ML pipelines.
Observability: Implement monitoring, logging, and alerting systems to track model performance and detect drift in production.
Continuous Innovation: Stay current with emerging ML frameworks, deep learning methods, and generative AI approaches to keep the platform at the cutting edge.
What We’re Looking For
Professional Experience: 4–8 years of experience as a Machine Learning Engineer or in a related applied ML role.
Programming Skills: Proficiency in Python (TensorFlow, PyTorch, scikit-learn) and strong skills in software engineering (data structures, algorithms, testing, version control).
ML Expertise: Experience with supervised/unsupervised learning, deep learning, NLP, or recommender systems.
Data Experience: Strong SQL skills and familiarity with big data tools (Spark, Hadoop, or cloud-native equivalents).
Cloud & Infrastructure: Hands-on experience with AWS, GCP, or Azure for large-scale training and deployment.
Systems Thinking: Ability to design reliable, scalable, and maintainable ML pipelines for production environments.
Collaboration: Strong communication skills and ability to work with cross-functional teams including product, engineering, and research.
Education: Bachelor’s or Master’s degree in Computer Science, Engineering, Statistics, or a related quantitative field; PhD a plus.
Why JoinThis is a rare opportunity to join a pre-IPO company at scale, where your work in machine learning will directly shape industry-leading products. You’ll work with cutting-edge technologies, collaborate with top engineers and researchers, and have the chance to influence both technical strategy and product direction. The company is on a hypergrowth path, and as a Machine Learning Engineer you’ll be a core part of delivering intelligent systems that define the next chapter of our success.About AndiamoTalent Partners for the AI Revolution. As a globally recognized staffing and consulting firm, we specialize in placing the top 2% of technology and go-to-market professionals with the world’s largest and most well-known companies.For over 20 years, we've maintained the status of tier-one vendor for firms such as Palantir, Amazon, Fluidstack, Bloomberg, Relativity Space, Firefly, MasterCard, Visa, Two Sigma, Citadel, as well as other major financial services firms, elite hedge funds, Google-backed tech start-ups, and major software firms.Our talent solutions include Permanent Placement, Contract Staffing, Executive Search, and Dedicated Recruiting Services (RPO). Find out more at www.andiamogo.com
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Seniority level
Mid-Senior level
Employment type
Full-time
Job function
Engineering and Information Technology
Industries
Staffing and Recruiting