We are looking for a Marketing Specialist with experience in Brand Communications to support and grow EPAM’s degree and non-degree education programs across international markets. The role focuses on content, communications, and community engagement, with close collaboration across product, marketing, and regional teams. This position requires a strong ability to work with text, a strategic understanding of brand communication objectives, and confidence in cross-functional and international collaboration.
responsibilities
Support the promotion and development of EPAM educational projects across international markets
Create and manage written communications, including social media content, articles, newsletters, and email campaigns
Coordinate community engagement activities across social platforms and community channels, including online events and collaborations
Plan and execute marketing and communication initiatives aligned with business goals and brand guidelines
Collaborate with educational product teams to translate product value into clear and consistent messaging
Work with international teams and external partners to ensure alignment and effective execution
Support the development of the department’s brand, both internally and externally
Conduct research and support online events, webinars, and knowledge-sharing initiatives
requirements
English level B2 (Upper-Intermediate) or higher
Confident communication skills in English
2+ years of experience in marketing, communications, or PR
Strong writing and editing skills across short- and long-form content
Strategic mindset with the ability to align communications with business objectives
Ability to work independently and manage multiple priorities
nice to have
Experience with international markets, particularly WCA
Background in IT, education, or technology-driven projects
Community or event management experience
Familiarity with AI tools and basic design tools (e.g., Figma, Canva)
Interest in continuous learning and professional development
We are seeking a highly skilled and experienced Senior Machine Learning Engineer to drive the development, deployment, and monitoring of cutting-edge machine learning solutions in a scalable cloud environment. You will collaborate with a cross-functional team to deliver end-to-end ML pipelines, ensure high-quality model performance, and implement robust monitoring for production systems.
responsibilities
Reproduce training environments with pinned dependencies and seeds, rebuild feature and label pipelines, and register models
Deploy SageMaker endpoints and batch jobs with autoscaling, execute shadow/canary strategies, and define rollback protocols
Set up ML experiments, Model Registry, and Feature Stores, integrating them into CI/CD workflows
Implement Model Monitor for drift and performance tracking, configure alerting mechanisms, and create comprehensive runbooks
Optimize pipelines for reliable model serving, ensuring low latency, high quality, and rollback readiness during hypercare
Collaborate with data engineers to build scalable data pipelines on S3/Snowflake for training and inference workflows
requirements
3+ years of hands-on experience in machine learning engineering, with a solid background in Python 3.x
Proficiency in PyTorch or TensorFlow, with a track record of building and deploying models in production
Expertise in AWS SageMaker, including Pipelines, Registry, Endpoints, and Model Monitor
Familiarity with MLflow or SageMaker Experiments for experiment tracking and artifact management
Strong skills in Docker for containerization of ML workloads
Experience with Feature Store solutions such as SageMaker Feature Store or Feast
English level B1+ for effective communication
nice to have
Proficiency in FastAPI or BentoML for lightweight API service development
Knowledge of ONNX for model optimization and cross-platform interoperability
Familiarity with distributed inference tools like Ray Serve or Triton
Experience with large-scale distributed training using Horovod or DeepSpeed
Understanding of Hugging Face Transformers for state-of-the-art NLP model implementation
We are searching for a Lead Machine Learning Engineer who will be responsible for designing ML models that undergo ongoing training and developing frameworks suited for data scientists. If you possess exceptional skills in developing and implementing production applications and data pipelines, consider applying for this position.
responsibilities
Oversee the migration of machine learning algorithms to a production setting and their integration within the company's existing systems
Create, manage, and improve the entire machine learning lifecycle from start to finish
Draft detailed specifications, documentation, and user manuals
Enhance SDLC processes, set up and manage CI/CD/CT frameworks
Implement mechanisms for the early detection of different types of drifts (data, concept, schema, etc.)
requirements
5+ years of enterprise software development experience
3+ years of Machine Learning experience
Qualifications in designing, constructing and launching production applications and data pipelines
Skills in developing highly resilient, scalable applications and systems powered by ML
Hands-on expertise in establishing SDLC best practices
Understanding of Python development
Familiarity with Cloud-native services (GCP, AWS, Azure) and Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
nice to have
Expertise in MLOps-related platforms and technologies
Experience in integrating ML models within multifaceted data-driven systems, IoT devices, or mobile devices
Proficiency in basic software engineering tools (CI/CD environments like Jenkins or BuildKit, PyPI, Docker, and Kubernetes)
As a Senior Machine Learning Engineer, you will lead the development of advanced AI models and machine learning pipelines to tackle complex challenges. Collaborating with cross-disciplinary teams, you will ensure the scalability and robustness of our AI systems. If you are eager to apply your machine learning expertise in a forward-thinking environment, we invite you to apply.
responsibilities
Design and build scalable machine learning algorithms and models to solve business problems
Develop and maintain robust data pipelines supporting ML model training and deployment
Collaborate effectively with data scientists and engineers to optimize machine learning solutions
Create and manage CI/CD workflows to support ML operations
Monitor and enhance the accuracy and performance of ML models over time
Analyze large datasets to generate insights aiding model development
Stay updated on the newest developments in machine learning and AI technologies
requirements
Bachelor’s degree in Computer Science, Engineering, or similar disciplines
At least three years of experience in machine learning engineering or related roles
Expertise in Python for developing machine learning models and data pipelines
Practical knowledge of CI/CD tools and practices for ML deployment
Strong familiarity with AWS machine learning and data processing services
English proficiency at B2 level or beyond, both written and spoken
nice to have
Experience using Snowflake for data storage and analytic tasks
Knowledge of advanced ML frameworks like TensorFlow or PyTorch
Exposure to MLOps practices and tools for managing machine learning workflows
We are seeking a highly skilled Senior Machine Learning Engineer to join our remote team. As a Senior Machine Learning Engineer, you will be responsible for designing and implementing machine learning solutions for our clients using your extensive experience in Data Science and Machine Learning Engineering. You will be working with large-scale datasets and using your expertise to develop and deploy industrial-scale ML solutions. You will also be responsible for communicating with client stakeholders on both the technical and business side to ensure delivery is client driven. If you have a passion for designing and implementing machine learning solutions, we encourage you to apply.
responsibilities
Design and implement machine learning solutions for clients using your expertise in Data Science and Machine Learning Engineering
Work with large-scale datasets and develop and deploy industrial-scale ML solutions
Communicate with client stakeholders on both the technical and business side to ensure delivery is client driven
Integrate ML solutions into cloud services such as AWS SageMaker, S3, and Lambda
Analyze and interpret data and provide clear and comprehensive reports
Collaborate with cross-functional teams to conceptualize, design, develop, and implement effective machine learning solutions
requirements
3+ years of experience in Data Science and Machine Learning Engineering
Strong understanding of Amazon Web Services (AWS) and experience with AWS SageMaker, S3, Lambda, and other cloud services
Experience in time series forecasting and working with R-based solutions
Experience with orchestration and experiment tracking tools such as AirFlow, MLFlow, and DVC
Ability to communicate effectively with client stakeholders on both the technical and business side
Fluent English language skills with an Upper-Intermediate level as a minimum
nice to have
Experience with Snowflake, R time series libraries, AWS CodePipeline, DataBricks, and k8s
We are seeking an experienced Senior Machine Learning Engineer to join our team and contribute to the development of advanced AI-driven solutions. In this role, you will design, implement, and optimize machine learning models and pipelines to solve complex business challenges. You will collaborate with cross-functional teams to drive innovation and ensure the scalability and efficiency of machine learning systems.
responsibilities
Design and develop scalable machine learning models and algorithms to address business needs
Build and maintain robust data pipelines to support model training and deployment
Collaborate with data scientists and engineers to refine and optimize ML solutions
Implement and manage CI/CD pipelines for machine learning workflows
Monitor and improve model accuracy and performance over time
Analyze large datasets to extract meaningful insights and support model development
Stay up-to-date with the latest advancements in machine learning and AI technologies
requirements
Bachelor's degree in Computer Science, Engineering, or a related field
At least 3 years of experience in machine learning engineering or a related role
Proficiency in Python for developing machine learning models and data pipelines
Hands-on experience with CI/CD tools and practices for deploying ML solutions
Strong knowledge of AWS services for machine learning and data processing
Fluent English skills, both written and spoken, at a B2 level or higher
nice to have
Experience with Snowflake for data storage and analytics
Familiarity with advanced frameworks like TensorFlow or PyTorch
Exposure to MLOps practices and tools for managing machine learning systems
We are seeking an experienced Senior Machine Learning Engineer to join our team and contribute to the development of advanced AI-driven solutions. In this role, you will design, implement, and optimize machine learning models and pipelines to solve complex business challenges. You will collaborate with cross-functional teams to drive innovation and ensure the scalability and efficiency of machine learning systems.
responsibilities
Design and develop scalable machine learning models and algorithms to address business needs
Build and maintain robust data pipelines to support model training and deployment
Collaborate with data scientists and engineers to refine and optimize ML solutions
Implement and manage CI/CD pipelines for machine learning workflows
Monitor and improve model accuracy and performance over time
Analyze large datasets to extract meaningful insights and support model development
Stay up-to-date with the latest advancements in machine learning and AI technologies
requirements
Bachelor's degree in Computer Science, Engineering, or a related field
At least 3 years of experience in machine learning engineering or a related role
Proficiency in Python for developing machine learning models and data pipelines
Hands-on experience with CI/CD tools and practices for deploying ML solutions
Strong knowledge of AWS services for machine learning and data processing
Fluent English skills, both written and spoken, at a B2 level or higher
nice to have
Experience with Snowflake for data storage and analytics
Familiarity with advanced frameworks like TensorFlow or PyTorch
Exposure to MLOps practices and tools for managing machine learning systems
We are seeking a Senior Machine Learning Engineer to join our innovative team. In this role, you will design, develop, and deploy machine learning models and solutions that address complex business challenges. You will collaborate with cross-functional teams to create scalable and efficient systems, leveraging cutting-edge technologies and techniques to drive impactful results.
responsibilities
Design and implement machine learning algorithms to solve real-world problems
Build and optimize pipelines for large-scale data processing and model training
Collaborate with data scientists and software engineers to integrate machine learning models into production systems
Develop and maintain scalable machine learning infrastructure to support model deployment and monitoring
Ensure the quality and reliability of machine learning solutions through rigorous testing and validation
Work with big data technologies to manage and process large datasets efficiently
Apply MLOps practices to streamline the development and deployment lifecycle of machine learning models
Establish and manage CI/CD pipelines for automating workflows and deployments
Monitor and troubleshoot deployed models to ensure optimal performance and accuracy
Stay up to date with the latest advancements in machine learning and related technologies
requirements
Bachelor’s degree in Computer Science, Engineering, Information Technology, or a related field
At least 3 years of hands-on experience as a Machine Learning Engineer, with a focus on production-grade systems
Proficiency in AWS for deploying and managing machine learning solutions in the cloud
Experience working with big data technologies for processing and analyzing large datasets
Familiarity with Databricks for collaborative data engineering and machine learning workflows
Strong understanding of MLOps practices for automating and scaling machine learning operations
Expertise in designing and implementing machine learning models for various applications
Practical experience with CI/CD tools like Jenkins and Airflow, and container orchestration tools like Kubernetes
Advanced programming skills in Python and Spark for building and optimizing machine learning systems
Fluent English communication skills, both written and spoken, at a B2 level or higher
nice to have
Knowledge of advanced deep learning frameworks or techniques for building complex models
Familiarity with cloud-native tools and services for improving scalability and system performance
We are looking for a Lead Machine Learning Engineer who will design ML models with continuous training and build frameworks for data scientists. Apply for the vacancy if you are highly competent in creating and deploying production applications and data pipelines.
responsibilities
Manage the transition of machine learning algorithms to the production environment and integration with the enterprise ecosystem
Design, maintain, and optimize the complete end-to-end machine learning life cycle
Design specifications, documentation and user guides
Contribute to the improvement of SDLC practices, establish and configure CI/CD/CT processes
Provide capabilities for early detection of various drifts (data, concept, schema, etc.)
requirements
5+ years of production experience in enterprise software development
3+ years of production background in Machine Learning
Qualifications in designing, building and deploying production applications and data pipelines
Competency in the development of highly available, largely scalable, ML-driven applications and systems
Hands-on expertise in the implementation of SDLC best practices
Knowledge of Python development
Familiarity with Cloud-native services (GCP, AWS, Azure) and Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
nice to have
Expertise in MLOps-related platforms/technologies
Production experience in integrating ML models into complex data-driven systems/IoT devices/mobile devices
Competency in basic software engineering tools (CI/CD environments such as Jenkins or BuildKit, PyPI, Docker, Kubernetes)
We are seeking a seasoned Senior Machine Learning Engineer to bolster our team. This role is ideal for a professional eager to leverage their AI and machine learning skills to drive transformative projects and solutions. The chosen candidate will play a pivotal role in enhancing and optimizing our advanced machine learning models and systems to meet the diverse demands of our applications.
responsibilities
Design machine learning models to address complex challenges
Collaborate with multidisciplinary teams to understand business needs and identify machine learning opportunities
Implement robust machine learning infrastructures in live environments
Evaluate and analyze data to ensure model accuracy and reliability
Improve the performance and efficiency of existing machine learning models
Guide and support junior engineers while leading machine learning projects
Stay informed about the latest trends and advancements in machine learning technologies
Incorporate new data sources to boost model capabilities
Produce detailed documentation on machine learning techniques and model structures
Share technical insights and model outcomes with stakeholders and team members
requirements
A minimum of 3 years of experience in Machine Learning Engineering, with expertise in AWS technologies
Proficiency in Amazon Bedrock for the creation and deployment of machine learning solutions
Extensive background in using Amazon SageMaker to develop and manage machine learning models
Comprehensive familiarity with Amazon S3 for effective data storage and handling in machine learning projects
Advanced expertise in Python for machine learning model development
In-depth knowledge of Natural Language Processing (NLP) and its practical applications
Demonstrated capability in applying Deep Learning techniques
Competency in Prompt Engineering to enhance model interaction
Skills in implementing Sentiment Analysis for practical use cases
Understanding of effective Model Evaluation for NLP to validate performance
Fluency in English at a B2 level or higher for seamless collaboration and stakeholder communication
nice to have
Understanding of other cloud platforms, including Google Cloud or Microsoft Azure
Proficiency in additional programming languages such as R or Java
Qualifications in machine learning, data science, or related disciplines
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