As part of the Enterprise Data & Intelligence (EDI) team, you will play a key role in enabling company-wide data-informed decision making. Business and Product teams rely on our data assets to analyze and optimize user adoption, growth, and revenue.

The ideal candidate will have a strong mix of technical and collaboration  skills. They should be able to quickly understand business priorities and proactively develop and enhance tools, automations and analytics that support those priorities.

This role is based in our Warsaw office with an office-centric hybrid schedule - in-office days are Monday, Tuesday, and Thursday. 

We offer a Contract of Employment (UoP) for our employees in Poland.

What you’ll achieve

• Design, implement and scale end-to-end data products that support growing data processing and analytical needs.
• Influence best practices in Databricks and cloud-based data engineering, driving innovation and adoption across teams.
• Establish trust and strong relationships across technical and business teams, ensuring alignment on data strategy and execution.
• Lead process automation efforts and proactively identify optimisation opportunities, improving data workflows and ensuring scalability.

About you

• 5+ years of hands-on experience in Data Engineering or Software Engineering.
• Degree in computer science, engineering or equivalent technical field experience.
• Proficient in cloud-based data processing and storage technologies like Databricks, Snowflake, AWS S3, Spark, Airflow.
• Fluent in SQL and proficient in at least one modern programming language (e.g., Python, Scala, Java).
• Proactive self-starter with a proven ability to identify opportunities, propose innovative solutions, and execute them effectively.
• Excellent communication skills, with the ability to clearly articulate complex technical concepts to non-technical stakeholders.
• Demonstrated curiosity about AI tools and emerging technologies, with a willingness to learn and leverage them to enhance productivity, collaboration, or decision-making.

What we offer

• Generous, transparent and fair compensation system (base salary and generous Restricted Stock Unit for Asana Inc.) 
• Contract of Employment (with 50% tax deductible costs for author’s rights usage for Engineers) 
• Health insurance with dental and travel coverage (Lux Med) 
• Lunch catering on the days that you work from the office
• Career growth budget 
• Home office setup budget 
• Gym/Fitness reimbursement
• Fertility healthcare and family-forming support with Carrot
• Mental health support in Modern Health
• Group life insurance
• MacBooks with all necessary accessories

For this role, the estimated base salary range is between 20,833 - 22,983 PLN gross monthly on the contract of employment (UoP). The actual base salary will vary based on various factors and individual qualifications objectively assessed during the interview process. The listed range above is a guideline, and the base compensation range for this role may be modified.

Our total compensation consists of base salary and equity (RSUs). 

#LI-Hybrid 

About the role

Starburst is looking for an experienced Staff Software Engineer to sit at the intersection of software engineering and data engineering — building the internal platforms, pipelines, and data products that power how we understand our customers and our business. You'll work across Starburst Enterprise and Starburst Galaxy, using our own technology to solve real problems at scale, while also contributing software that other teams depend on.

Because data engineers are one of our primary target personas, you'll bring a uniquely valuable perspective: you'll use our products daily and feed that experience directly back into how we build and improve them. You'll work closely with a dynamic, talented, globally distributed team, writing production-quality software alongside building reliable data systems — with a consistent emphasis on quality, maintainability, and speed to insight.

As a Staff Software Engineer at Starburst you will:

• Design, build, and operate a high-quality data lake and the software systems that feed it, supporting product management, finance, customer support, and engineering
• Write production-grade software — services, APIs, tooling, and automation — that enables data workflows and integrations at scale
• Find innovative ways to use Trino and Starburst to solve complex data management and software architecture challenges
• Collaborate with technical leads, product managers, and data analysts to build robust data products and analytics
• Leverage AI to democratize access to datasets for users throughout Starburst, including building and maintaining the software infrastructure that makes this possible
• Enable dataset preparation and model evaluation for Starburst's AI projects
• Define and evolve engineering processes and best practices that span both software and data domains, with a focus on reliability and actionable results
• Work closely with leaders across teams to iterate on data architecture and the software systems that implement it, keeping quality high at every layer
• Identify emerging patterns in data management and software engineering, and work with Starburst's product teams to bring those innovations to market

Some of the things we look for

• A Trino enthusiast looking to push the bounds in an AI future
• At least 7 years of combined experience in software engineering and/or data engineering, with genuine depth in both
• Strong software engineering fundamentals: writing clean, testable, well-reviewed code in Java, Python, or Scala
• Experience building and optimizing data pipelines using Trino, Spark, dbt, and related frameworks
• Experience designing and building backend services, APIs, and data platform components
• Experience managing data and application infrastructure in public clouds, particularly AWS (EMR, EC2, S3, IAM); multi-cloud experience (GCP/Azure) is a plus
• Experience using and managing orchestration frameworks such as Apache Airflow or Dagster
• Knowledge of RAG and other design patterns for AI-powered applications
• Fluency in SQL and comfort moving between SQL and general-purpose programming as the task demands
• Experience building API integrations for extracting data from third-party sources
• Knowledge of data modeling techniques appropriate for modern data lakes
• Proficiency with Configuration-as-Code and Infrastructure-as-Code tools such as Pulumi, Terraform, and/or Ansible
• A track record of shipping reliable software and data systems on time, with disciplined practices around testing, code quality, and review
• Strong written and verbal communication skills, with the organizational ability to coordinate across teams

Where could this role be based?

• San Francisco, US

The Senior Data Operations Engineer will support the management and optimization of the company’s data systems and processes, reporting directly to the Data Operations Lead.

This role requires a technically proficient individual with strong analytical skills to ensure data integrity, accessibility, and security across the data platform. The ideal candidate will have hands-on experience in data management, a keen eye for detail, and the ability to work collaboratively with different stakeholders.

✅ Responsibilities:

Data Management and Maintenance

• Assist in developing and enforcing policies for effective data management.
• Ensure data accuracy, consistency, and security through regular maintenance and monitoring.
• Support the implementation of data quality standards and maintain data governance practices.

Operations Support

• Manage and optimise data pipelines and ETL processes to ensure smooth and efficient workflows.
• Troubleshoot and resolve data-related issues promptly to minimise downtime.
• Monitor the availability and performance of data systems and tools, ensuring they meet operational standards.

Collaboration and Communication

• Work closely with the Data Operations Lead, Data Engineering, Business Intelligence, Analytics, and Business teams to support data initiatives.
• Collaborate with vendors and partners for data-related services as directed by the Data Operations Lead.
• Communicate effectively with team members and stakeholders to ensure alignment on data projects and initiatives.

Compliance and Security

• Assist in ensuring compliance with various jurisdictions and regulations, as well as industry best practices.
• Implement and maintain data security measures to protect sensitive information.
• Participate in regular audits and assessments to identify and mitigate risks.

Day-to-Day Activities

• Check the status of data jobs to ensure they are running as expected and troubleshoot any issues.
• Monitor and maintain data pipelines, ensuring data flows smoothly between systems.
• Conduct data verification and integrity checks to maintain high data quality and accuracy.
• Perform reconciliations across various data sources to identify and resolve discrepancies.
• Proactively perform data audits to ensure data accuracy and compliance.
• Suggest and build improvements in data accuracy and reconciliation frameworks.
• Work collaboratively with the data team to address any operational challenges and support data-driven initiatives.

On-Call Rotations

• On-Call Rotations - During specific weeks, you need to be available 24/7 in case of incidents.

✅ Requirements:

• At least 3 years of Python engineering experience;
• At least 2 years of experience with SQL;
• 1+ years of experience in data management and data operations roles.
• Proficiency in SQL, Python, or other data manipulation languages.
• Experience with cloud data warehousing solutions (e.g., Snowflake, Redshift, BigQuery).
• Familiarity with ETL tools (e.g., Apache NiFi or Airflow).
• Knowledge of cloud platforms (AWS, Azure, Google Cloud).
• Strong problem-solving skills and attention to detail.
• At least 1 year of experience in PowerBI (or similar);
• Excellent communication and teamwork skills.

Nice to have:

• Experience with data quality management.
• Experience working with agile.
• Understanding of data governance frameworks and practices.
• Certifications in relevant data management or cloud platform technologies.

✅ We offer excellent benefits, including but not limited to:

🚀 Career growth opportunities in an international and dynamic environment;
📚 Opportunity to develop language skills with partial compensation for language courses;
🎁 Special gifts for birthdays, weddings, and newborns;
🏝️ 20 working days of paid annual vacation, plus paid sick leaves;
🍲 Office snacks and refreshments;
🏋️‍♂️ Sports package to support a healthy lifestyle;
🩺 Comprehensive medical insurance for you and your partner;
📍 Comfortable office with great facilities in a prime location;
 🎉 Exciting corporate events, team-building activities, and international company parties.

Evoplay is one of the leading iGaming providers, recognized for its innovative approach to game development and technological solutions. The key to this success is the teamwork of like-minded people who are passionate about a common goal and love games.

Our mission is to surprise not only the iGaming market but the entire entertainment industry with our interesting and unique products. Our game portfolio of 150+ titles, where each is a unique and exciting story, is presented all over the world, including Europe, Latin America, Asia, and the CIS.

We are looking for a strong specialist who goes beyond data processing — someone who understands the business behind the data and can influence decisions through analytics. This role requires autonomy, fast learning, and full ownership of data quality and analytical outputs.

Requirements

• Advanced Python and SQL (query optimization, complex data transformations, large-scale data handling)
• Hands-on experience with ClickHouse or other columnar databases
• Strong background in building ETL/ELT pipelines (ingestion, transformation, orchestration). Experience with Airflow is a plus.
• Solid understanding of Data Warehouse architecture
• Strong Data QA skills (identifying and resolving data issues)
• Experience with Power BI (building and maintaining reports)
• Ability to quickly understand business logic and translate it into data models
• High attention to detail
• English — B2 or higher (working proficiency)

Nice to Have

• Experience with data governance implementation
• Experience in high-load systems
• Experience working with product and business teams

Responsibilities

• Own data quality: identify, analyze, and fix data issues
• Translate business processes into reliable data structures
• Build and optimize ETL pipelines
• Deliver clean and structured data for analytics and BI
• Handle AdHoc analytical requests under tight deadlines
• Maintain and improve Power BI reporting
• Automate repetitive tasks
• Provide analytical support
• Train users on BI tools

What we offer

• Corporate psychologist;
• Gifts for significant occasions;
• Legal support;
• Flexible working hours;
• Direct access to C-level and opportunity to suggest new business ideas and drive changes.

If you are ready to work in a dynamic team, passionate about the product, technology, and the world of entertainment, we’re waiting for your CV and portfolio to schedule an online/offline meeting and get to know each other better!

Your CV will be carefully reviewed by our TA department, and if it meets the requirements of the position, we will contact you within 3 business days to discuss the possibility of scheduling an interview.

❗️IMPORTANT: This position is office based for our office in Warsaw, Poland.

❗️We can provide relocation assistance if you're outside of the city or country.

We are seeking a highly skilled Data Engineer with expertise in managing, designing, and optimizing data pipelines utilizing Apache Airflow, Snowflake, and Apache Kafka.
This individual will play a pivotal role in architecting robust, scalable, and efficient data solutions, ensuring the integrity, reliability, and accessibility of our data infrastructure

✅ Responsibilities:

• Develop and implement data models to support business requirements, optimizing for performance and scalability;
• Design, build, and maintain scalable data pipelines using Apache Airflow;
• Implement and maintain Kafka-based streaming data pipelines for real-time data processing and integration with various systems;
• Integration to third party databases and APIs;
• Establish monitoring, alerting, and maintenance procedures to ensure the health and reliability of data pipelines;
• Collaborate with cross-functional teams including data scientists, analysts, and stakeholders to understand data requirements.
  
  

✅ Requirements:

• Proficiency in Python, SQL, and experience with data manipulation and transformation;
• Data warehouse and data modeling techniques;
• Experience in designing, building, and maintaining complex data pipelines using Airflow;
• Proven track record in data engineering roles, with a focus on designing and implementing scalable data solutions using Snowflake or Redshift;
• In-depth understanding and practical experience in implementing Kafka-based streaming architectures for real-time data processing.
  
  

✅ We offer excellent benefits, including but not limited to:

✔️Career growth opportunities in an international and dynamic environment;

✔️Opportunity to develop language skills with partial compensation for language courses;

✔️Special gifts for birthdays, weddings, and newborns;

✔️20 working days of paid annual vacation, plus paid sick leaves;

✔️Office snacks and refreshments;

✔️Sports package to support a healthy lifestyle;

✔️Comprehensive medical insurance for you and your partner;

✔️Comfortable office with great facilities in a prime location;

✔️Exciting corporate events, team-building activities, and international company parties.

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As part of our team, you will:

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

We’ll be happy to have you on our team if you have:

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

#LI-HYBRID
#LI-MR1

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving to make the strongest, most effective developer tools on earth. Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs.

We’re building multi-step coding agents that can understand large codebases, plan changes, call tools, and iterate with the user. As a Research Engineer in the Agentic Models team, you’ll be responsible for the models, training loops, and evaluation pipelines that power these agents.

You’ll work at the intersection of SFT and RL-style post-training, and product-driven evaluation, using our distributed GPU and MapReduce clusters to ship models into JetBrains products.

As part of our team, you will:

• Design, implement, and maintain SFT and RL post-training pipelines for multi-step coding agents.
• Train and adapt LLMs for agent workflows, including planning, tool use, and multi-step interactions inside JetBrains IDEs.
• Build and develop evaluation and simulation environments where coding agents can act, be measured, and compared on realistic developer tasks.
• Design evaluation frameworks and metrics for agent behavior, analyze traces and logs, and close the loop from evaluation back into training, data, and reward design.
• Analyze training and evaluation results to propose and implement improvements to model architectures, training recipes, and datasets.
• Work with large-scale infrastructure, including distributed training on GPU clusters and large MapReduce-style data processing for pre-training and fine-tuning datasets.
• Collaborate closely with research, product, and infrastructure teams to turn high-level product visions into concrete models, experiments, and shipped features. 

We’ll be happy to bring you on board if you have:

• Extensive hands-on experience training LLMs (pre-training, fine-tuning, or post-training) in a research or production setting.
• Deep expertise in modern deep learning frameworks such as PyTorch, and specialized LLM training stacks (e.g. Megatron, NeMo, verl, or similar).
• Strong theoretical and practical understanding of LLM fundamentals: architectures, tokenization, data pipelines, batching, mixed precision, distributed training, and debugging unstable runs.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A product-aware mindset – you care about how developers actually use agents and can translate product needs and failure modes into modeling and evaluation work.
• At least 3 years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as Kubeflow, Dagster, Airflow, ZenML, and/or job schedulers like Kubernetes or SLURM.
• Large-scale data and training pipelines, e.g. MapReduce-style clusters, multi-node GPU training, or workloads on the order of 1M+ CPU/GPU hours.
• Designing and maintaining evaluation pipelines for LLMs or agents, including metrics, dashboards, experiment tracking, and automated regression checks.
• AI agent development, such as tool-using agents, planners, or multi-step coding workflows, and familiarity with agentic frameworks or patterns.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.
• Inference optimization and serving optimized models in production.

#LI-KP1

We are looking for a Senior ML Platform Engineer to join our ML Platform team to build, evolve and scale AI Infrastructure that powers Bolt's intelligent services

With over 200 million customers in 50+ countries, Bolt is one of the fastest-growing tech companies in Europe and Africa. And it's all thanks to our people.

We believe in creating an inclusive environment where everyone is welcome, regardless of race, colour, religion, gender identity, sexual orientation, age, or disability.

Our ultimate goal is to make cities for people, not cars, and we need your help to achieve this mission!

The ML Platform Team makes ML/AI easy at scale. We streamline development, testing and deployment of ML/AI systems for hundreds of real-time algorithms. 

We own training orchestration, an inference software stack and infrastructure, and a Feature Store, including VectorSearch and RAG tooling. We develop LLM tools and CI/CD for ML, covering the whole range of ML infrastructure needs.

Our tech stack includes TypeScript, Python, Spark (batch and structured streaming), Airflow, n8n, MLflow, LiteLLM, AWS SageMaker, Redis, Elasticsearch, Docker, Kubernetes, AWS (S3, EKS), Terraform, Great Expectations. 

• Designing, building, and optimising components of Bolt’s ML Platform.
• Optimise and extend our in-house Feature Store Platform serving billions of data points in real-time.
• Tune infrastructure (k8s and AWS) and build automations to achieve the best cost-performance.
• Proactively solve technical challenges, discover and build new features, enabling develop efficiency.
• Support our internal users and help with troubleshooting, and turn user problems into scalable solutions.
• Raise our product and technical quality bar, promoting software engineering best practices.

• 5+ years of experience in Software Engineering, out of which 2+ in ML/MLOPS/AI Engineering.
• Experience in leading and delivering complex cross-team projects.
• Production experience with Python, Spark, and Kubernetes.
• Experience in MLOPS and AI ecosystem, and developing end-to-end ML/AI solutions at scale.
• You strive for technical excellence while staying pragmatic to achieve outcomes for the users.

Experience is great, but what we really look for is drive, intelligence, and integrity. So even if you don’t tick every box, please consider applying!

• Accelerate your professional growth with unique career opportunities.
• Enjoy a rewarding salary and stock options, knowing that as Bolt succeeds, so do you.
• Take care of your physical and mental health with our wellness perks.
• Celebrate 5 years at Bolt with a 1-month paid sabbatical to recharge.
• Connect with colleagues at annual company events and smaller team gatherings.
• Balance flexibility and in-person collaboration with our hybrid model, including at least 12 monthly in-office days.

*Some perks may differ depending on your location and role.