Let’s get started
By clicking ‘Next’, I agree to the Terms of Service
and Privacy Policy
Jobs / Job page
Machine Learning Engineer (LLMs) image - Rise Careers
Job details

Machine Learning Engineer (LLMs)

 

NOTICE: ONLINE RECRUITMENT PROCESS

LOCATION: REMOTELY FROM POLAND

 

SALARY:

Mid: 23 500 - 32 000 PLN gross/monthly
Senior: 26 000 - 35 000 PLN gross/monthly

 

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.

WHAT YOU'LL DO

  • Operationalization of Machine Learning Models

    • 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.

  • Tooling, Infrastructure & Experimentation Support

    • 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.

  •  Continuous Learning

    • 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.

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.

WHAT YOU GET BY JOINING BRAINLY

  • We want to see you grow along with us – you will have 800$ per year for personal development, extra time for attending conferences and workshops, and unlimited access to an online learning platform (courses from Coursera, Udacity, Udemy, Harvard ManageMentor, Busuu, and many others!)

  • Health is important, which is why at Brainly, we fully cover private health & dental care packages for you and your family and provide you with a sport card (Multisport Plus) 

  • You will also get an access to online individual psychological consultations with professionals in English, Polish & Ukrainian via the Mental Health Helpline

  • Your personal concierge AskHenry will support you in your daily duties, eg. planning your dream vacation

  • You can join internal communities and contribute to charity, diversity and inclusion initiatives, take part in great internal events or represent Brainly at conferences or meet-ups

  • We also provide stock options

 

By sending us your application you agree that Brainly sp. z o.o. will process your personal data to participate in this recruitment process. If you want to know more about how Brainly processes your personal data please click here.

 

ABOUT BRAINLY

Brainly is the #1 AI education tool in the world, with a vision to give every student in the world access to personalized learning, no matter their background or resources. 

Powered by its full-service AI Learning Companion™, Brainly is relied upon by more than 10 million students, parents and teachers every day for personalized, on-demand academic assistance. The platform provides world-class homework help, test prep and tutoring that is verified for accuracy and customized to each student based on their learning style. 

Founded in 2009, Brainly operates in the US, Europe, Asia and Latin America, and is backed by Prosus, Point Nine Capital, General Catalyst, Runa Capital, Learn Capital and Kulczyk Investments.

Learn more at www.brainly.com.

Brainly Glassdoor Company Review
3.2 Glassdoor star iconGlassdoor star iconGlassdoor star icon Glassdoor star icon Glassdoor star icon
Brainly DE&I Review
No rating Glassdoor star iconGlassdoor star iconGlassdoor star iconGlassdoor star iconGlassdoor star icon
CEO of Brainly
Brainly CEO photo
Michał Borkowski
Approve of CEO

Average salary estimate

$85000 / YEARLY (est.)
min
max
$63000K
$107000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Machine Learning Engineer (LLMs), Brainly

If you're ready to make waves in the world of education technology, consider joining Brainly as a Machine Learning Engineer (LLMs)! At Brainly, our mission is to transform learning through innovative AI solutions, and we need passionate individuals like you to bring this vision to life. In this remote role, your primary focus will be on operationalizing machine learning models that guide millions of students across the globe. Imagine designing and implementing scalable infrastructure to support our AI-driven platform – how exciting is that? You'll collaborate with a talented team of Senior ML Engineers, Data Scientists, and AI Data Analysts as you tackle real-world educational challenges. Responsibility comes with the territory, as you'll be steering the deployment and maintenance of AI models, automating workflows, and ensuring our solutions remain at the cutting edge of technology. We value self-motivated learners who aren't afraid to embrace challenges; if you have experience with deep learning models and a solid grasp on Python, you're already ahead of the game! With additional perks like a personal development budget and health benefits, Brainly provides a supportive environment for growth. Come join us in shaping the future of learning and create impactful solutions that truly make a difference!

Frequently Asked Questions (FAQs) for Machine Learning Engineer (LLMs) Role at Brainly
What are the core responsibilities of a Machine Learning Engineer at Brainly?

As a Machine Learning Engineer (LLMs) at Brainly, you'll play a vital role in operationalizing machine learning models throughout their lifecycle. This involves developing and maintaining scalable infrastructures, automating workflows for model retraining, and ensuring the seamless integration of ML artifacts into production systems. You will also support data scientists in refactoring and optimizing code to maintain high standards of quality, reusability, and scalability.

Join Rise to see the full answer
What qualifications are required for the Machine Learning Engineer position at Brainly?

To qualify for the Machine Learning Engineer (LLMs) position at Brainly, candidates should possess at least 3 years of experience in deploying and maintaining machine learning models in production. Proficiency in Python, knowledge of cloud computing (especially AWS), and experience with deep learning frameworks like TensorFlow and PyTorch are essential. Familiarity with advanced ML pipelines and parallel computing will significantly strengthen your application.

Join Rise to see the full answer
How does Brainly support the professional development of Machine Learning Engineers?

Brainly is committed to fostering your growth as a Machine Learning Engineer. You'll have access to an annual budget of $800 for personal development, extra time to attend conferences and workshops, and unlimited access to an extensive online learning platform featuring courses from renowned sources such as Coursera and Harvard ManageMentor.

Join Rise to see the full answer
What technologies and tools are Machine Learning Engineers at Brainly expected to use?

Machine Learning Engineers at Brainly are expected to be proficient in technologies such as AWS for deploying and managing ML models. Familiarity with frameworks like TensorFlow, PyTorch, and tools for data management like Kafka or Spark is advantageous. Knowledge of CI/CD practices and modern Python tools is also essential to ensure successful workflows and project execution.

Join Rise to see the full answer
What team dynamics can a Machine Learning Engineer expect at Brainly?

At Brainly, you can look forward to a collaborative team environment where you will work closely with Senior ML Engineers, Data Scientists, and AI Analysts. Communication and teamwork are emphasized as you jointly tackle technical challenges and optimize AI models. Brainly nurtures a culture of continuous learning, so expect to grow alongside accomplished professionals in the AI field.

Join Rise to see the full answer
Common Interview Questions for Machine Learning Engineer (LLMs)
Can you describe your experience with deploying machine learning models in production?

When answering this question, reflect on your specific experiences deploying models, discussing the frameworks and technologies you used. Highlight any scaling challenges you overcame and the strategies you implemented to ensure model stability and performance efficiency.

Join Rise to see the full answer
How do you approach optimizing machine learning workflows?

Your answer should outline your strategies for increasing efficiency during the ML lifecycle. Discuss automating processes, implementing CI/CD practices, and ideas for reducing manual intervention while ensuring accuracy and reliability in model deployments.

Join Rise to see the full answer
What tools and frameworks do you prefer for machine learning, and why?

Detail your preferred ML tools and frameworks, explaining how they fit into your development workflow. Consider discussing aspects like ease of use, community support, scalability, or performance features that make these tools advantageous in different scenarios.

Join Rise to see the full answer
Describe a challenging ML project you worked on. What obstacles did you face, and how did you overcome them?

This question is your chance to tell a compelling story. Describe the project context, specific challenges faced (like data quality, model accuracy, etc.), and the innovative solutions you designed. Show how these experiences have prepared you for the challenges in the role at Brainly.

Join Rise to see the full answer
How do you ensure the scalability of machine learning models?

Discuss strategies for ensuring modeling scalability, such as using cloud solutions for resource allocation, designing modular architectures, or implementing batch processing techniques. Back your points with examples from previous work.

Join Rise to see the full answer
What role does versioning play in your machine learning projects?

Explain how versioning is crucial in machine learning projects for tracking changes, model evolution, and reproducibility. Share your experience with tools or methodologies you use for version control, ensuring models can be easily maintained and analyzed over time.

Join Rise to see the full answer
How do you keep up with the latest advancements in AI technology?

Here, it’s important to mention how you actively engage with the AI community. Talk about attending conferences, following key authors and researchers on social media, subscribing to relevant journals, or participating in forums and discussions. This shows your commitment to staying updated in the fast-moving tech landscape.

Join Rise to see the full answer
Can you give an example of a time you automated a tedious process?

Use this opportunity to describe a specific process that you automated, detailing your motivations and the tools used. Focus on the impact of this automation, such as saved time, reduced errors, or improved outcomes for subsequent projects.

Join Rise to see the full answer
What methodologies do you implement for model evaluation?

Talk about your approach to model evaluation, highlighting techniques like cross-validation and performance metrics used to ensure that your models meet success criteria. Discuss how you adapt your evaluation strategies based on specific project needs.

Join Rise to see the full answer
How do you prioritize tasks in a fast-paced environment?

Discuss your methods for task prioritization, including your criteria for assessing urgency and importance. Providing examples of how you've managed competing deadlines or multiple projects simultaneously will provide a strong illustration of your organizational skills.

Join Rise to see the full answer
Similar Jobs
Photo of the Rise User
Arista Networks Hybrid United States , United States , United States
Posted 3 hours ago
Photo of the Rise User
Posted 5 days ago
Inclusive & Diverse
Rise from Within
Mission Driven
Diversity of Opinions
Work/Life Harmony
Transparent & Candid
Growth & Learning
Fast-Paced
Collaboration over Competition
Take Risks
Friends Outside of Work
Passion for Exploration
Customer-Centric
Reward & Recognition
Feedback Forward
Rapid Growth
Medical Insurance
Paid Time-Off
Maternity Leave
Mental Health Resources
Equity
Paternity Leave
Fully Distributed
Flex-Friendly
Some Meals Provided
Snacks
Social Gatherings
Pet Friendly
Company Retreats
Dental Insurance
Life insurance
Health Savings Account (HSA)
Photo of the Rise User
Inclusive & Diverse
Collaboration over Competition
Fast-Paced
Growth & Learning
Empathetic
Photo of the Rise User
Posted 6 days ago
Photo of the Rise User
Rackspace Remote United States - Remote
Posted 11 days ago

Brainly is the place to learn - for students, by students. We are the world’s largest social learning community bringing middle school and high school students, parents and teachers together to make learning outside the classroom highly engaging, ...

8 jobs
MATCH
VIEW MATCH
FUNDING
DEPARTMENTS
SENIORITY LEVEL REQUIREMENT
TEAM SIZE
EMPLOYMENT TYPE
Full-time, remote
DATE POSTED
March 13, 2025

Subscribe to Rise newsletter

Risa star 🔮 Hi, I'm Risa! Your AI
Career Copilot
Want to see a list of jobs tailored to
you, just ask me below!