Machine Learning Engineer

A bit about us:

Tabnine is a world leader in AI-powered code completion, supporting more than 30 languages in 15 IDEs. Our team works tirelessly to build the tools that help the dev community write twice the code in half the time. Tabnine is trusted by over 1 million developers around the globe, and we're growing fast! Our production setup is one of the most advanced and efficient in the industry, enabling us to deliver language models at an unprecedented scale and quality. We are committed to staying at the forefront of AI and NLP, and we are excited about the opportunities that lie ahead.

A bit about the job:

Tabnine is set to revolutionize software development by injecting AI into all stages of the lifecycle. As a machine learning engineer, you will be in charge of designing, training, and deploying state-of-the-art neural models for development-related tasks. In Tabnine, ML is part of the core product, and your work has the potential to immediately impact millions of software developers.

Requirements:

Requirements:



2+ years of hands-on experience designing, training, and deploying machine-learning models
MSc or higher in Computer Science / Mathematics / Statistics or equivalent from a university
Practical experience with Natural Language Processing (NLP) and LLMs
Experience with data acquisition, data cleaning, and data pipelines
A passion for building products and helping people, both customers and colleagues
All-around team player, fast, self-learning individual

Responsibilities:

Responsibilities:



Innovation and Research: Spearheaded innovative research initiatives at the intersection of machine learning and software engineering. Pioneer new algorithms, models, and techniques that enhance developer productivity, code quality, and collaboration.
Product Impact: Implement research insights as product features that have a significant impact on our huge customer base.
Advanced Model Development: Develop complex machine learning models tailored to software engineering tasks. Create solutions that encompass code understanding, completion, recommendation, and other intelligent coding assistance functionalities.
Prototyping and Experimentation: Rapidly prototype and experiment with cutting-edge ideas. Validate hypotheses through empirical research and data-driven methodologies. Iterate on models to achieve exceptional performance.
Collaboration: Collaborate closely with cross-functional teams, including engineers, designers, and product managers.

Nice to have:

Nice to have:



3+ years of development experience with a passion for excellence
Strong experience in PyTorch
Experience with reinforcement learning techniques
Experience with training and deploying in Kubernetes
Experience with training and deploying LLMs
Experience with model optimizations (quantization, pruning, etc.)
Experience working at an early-stage startup
Experience working on modern, high-scale, production-grade projects