Machine Learning Engineer

1 day ago

Remote Kraków Wrocław Poznań Warszawa Rzeszów Gdańsk, Czech Republic Brainly Full time

WHAT IS REQUIRED

  • 3+ years experience with deployment and maintenance of Machine Learning models in production.
  • Experience in deploying and maintaining Deep Learning models, particularly Large Language Models (LLMs).
  • Strong command of writing production-level code in Python, with a focus on best engineering practices, in particular for training & deploying models.
  • PyData stack along with quick frontend frameworks e.g. streamlit.
  • Proven expertise in Cloud Computing (preferably AWS and services like IAM, EC2, S3, ECR, EKS, Redshift, Athena, Glue, Lambda, SecretManager) for storage, data pipelines, ML pipelines, and ML deployment.
  • Machine Learning frameworks such as: Tensorflow, PyTorch, JAX, scikit-learn, Transformers (HuggingFace).
  • Proven track record of development of data and machine learning pipelines.
  • Knowledge of Linux/Unix system, shell scripting.
  • Parallel computing (multi-processing, async, GPUs, types of AI parallelism).
  • Culture of DevOps and high-quality software standards.
  • Fluency in English.

WHAT IS PREFERRED

  • An academic degree in STEM (science, technology, engineering, mathematics) or a related field.
  • Hands-on experience with large-scale serving of ML models (millions of requests/day).
  • Hands-on experience with Kubernetes (deployment management, package manager e.g. Helm) and microservices.
  • Modern Python tools (e.g. ruff, uv, tox, pre-commit).
  • CI/CD (e.g. GitHub Actions, AWS CodePipeline).
  • IaaC frameworks  (Terraform, CloudFormation, Pulumi).
  • Familiarity with basics in Data Engineering (e.g. SQL and NoSQL, data streaming, Apache Spark, Snowflake).
  • Modern model serving frameworks (torchserve, NVIDIA Triton).
  • Familiar with agile development and lean principles.

WHAT WILL BLOW OUR MINDS

  • Experience with Flyte.
  • Knowledge of Golang.

ROLE OVERVIEW

At Brainly, we are on a mission to revolutionize learning through AI, helping millions of students worldwide gain confidence in their educational journey. As part of our AI-driven vision, we are committed to building cutting-edge solutions that enhance accuracy, reliability, and effectiveness of our AI-powered platform.

Benchmarking of AI Models (BEAM) Team plays a crucial role in ensuring high-quality performance of Brainly’s AI solutions. We are focused on designing and implementing robust evaluation pipelines and incremental improvements of AI solutions for real-world educational use cases. By developing comprehensive benchmarks, scalable evaluation pipelines, and iterative AI improvements, we ensure that Brainly’s AI components continually evolve to meet the highest standards of accuracy and effectiveness.

The Role

This is a highly technical individual contributor role within the Benchmarking of AI Models (BEAM) Team, working closely with Senior ML engineers, Data Scientists and AI Data Analysts to ensure seamless deployment and evaluation of AI models at scale. As a Machine Learning Engineer, you will be responsible for AI models deployment, creation and maintenance of scalable and reliable infrastructure and supporting the transition of research code into production-ready solutions. Your work will involve design reviews, best practice implementation, and rigorous code evaluation to ensure stability and efficiency of AI deployments.

Are you motivated to learn quickly and grow in the areas required to succeed in this job? Are you passionate about automating workflows? Do you take ownership of problems and challenges from beginning to end? Do you maintain a positive attitude and a willingness to tackle challenges and complex problems? Do you have a team-player mindset and strong communication skills? Are you highly self-organized? If you answered yes to these questions, you might just be the perfect candidate for this role

The ideal candidate is a skilled ML Engineer with a passion for AI-driven innovation, cloud infrastructure, and scaling machine learning models to real-world applications.

,[Orchestration of the entire ML model lifecycle, from development and deployment to monitoring, maintenance, and optimization ensuring scalability, efficiency, and reliability., Implementation of automated workflows for model retraining, versioning, and performance tracking to ensure long-term stability., Transformation of Machine Learning artifacts into production systems and services maintaining robust integration with existing engineering infrastructure., Design and implementation of tools, frameworks, and infrastructure to enhance efficiency of Data Scientists and other stakeholders simplifying areas such as model training and evaluation, data annotation, and processing. , Working with large-scale datasets in structured and ad-hoc exploratory setups to support both creation of well-organized data pipelines and rapid experimentation and prototyping., Supporting Technical Lead and Data Scientists in refactoring and optimizing research code, ensuring high-quality, reusability, and scalability of delivered solutions bridging the gap between AI experimentation and real-world deployment., Staying up to date with cutting-edge advancements in AI technology, including state-of-the-art models, algorithms, tools, and frameworks (both models/algorithms and tools/libraries/SaaS/APIs, etc.). Exploring opportunities to incorporate new methodologies, libraries, and services that enhance Brainly’s AI capabilities.] Requirements: Python, Cloud, LLMs, Kubernetes Additionally: Sport subscription, Training budget, Private healthcare, Dental Care Package, Stock options, AskHenry, Mental Health Helpline.

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