Machine Learning Engineer - Remote Remote Canada
Machine Learning Engineer - Remote Description
Job #: 74925
EPAM is a leading global provider of digital platform engineering and development services. We are committed to having a positive impact on our customers, our employees, and our communities. We embrace a dynamic and inclusive culture. Here you will collaborate with multi-national teams, contribute to a myriad of innovative projects that deliver the most creative and cutting-edge solutions, and have an opportunity to continuously learn and grow. No matter where you are located, you will join a dedicated, creative, and diverse community that will help you discover your fullest potential.
You are strategic, resilient, engaging with people and a natural self-starter. You have a passion for solving complex problems. If this sounds like you, this could be the perfect opportunity to join EPAM as a Machine Learning Engineer. Scroll down to learn more about the position’s responsibilities and requirements.
Req. #306883212
#LI-DNI
#LI-DNP
Description
You are strategic, resilient, engaging with people and a natural self-starter. You have a passion for solving complex problems. If this sounds like you, this could be the perfect opportunity to join EPAM as a Machine Learning Engineer. Scroll down to learn more about the position’s responsibilities and requirements.
Req. #306883212
#LI-DNI
#LI-DNP
What You’ll Do
- Responsible for the transition of machine learning algorithms to production environment and integration with enterprise ecosystem
- Design, create, maintain, troubleshoot, and optimize the complete end-to-end machine learning life cycle, which includes:
- machine-learning model optimization
- data preparation
- feature extraction
- model performance monitoring
- AB/Canar/Bluegreen testing
- Integration with Enterprise ecosystem/IoT devices/Mobile devices
- Write specifications, documentation, and user guides for developed solutions
- Build frameworks for data scientists to accelerate the development of production-grade machine learning models
- Collaborate with data scientists and engineering team to optimize the performance of ML pipeline
- Aid In improvement of SDLC practices
- Exploration of new tools and techniques and propose improvements
- Establish and configure CI/CD/CT processes
- Design and maintain ML models continuous training
- Provide capabilities for early detection of various drifts (data, concept, schema)
- Continuously identify technical risks and gaps, devise mitigation strategies
- Identify and eliminate technical debt in machine learning systems
Requirements
- Experience in Enterprise Software Development for 5+ years
- Solid background in Machine Learning for 3+ Years
- Experience with designing, building, and deploying production applications and data pipelines
- Experience in development of highly available, largely scalable, ML driven applications and systems
- Experience with cloud native services: GCP, AWS, Azure
- Able to work closely with customers and other stakeholders
- Strong knowledge and experience in Python development
- Deep understanding of Python ML ecosystem (pytorch, tensorflow, numpy, pandas, sklearn, XGBoost)
- Hands-on experience in implementation of Data Products
- Deep understanding of data preparation and feature engineering
- Understanding of Apache Spark Ecosystem (Spark SQL, MLlib/Spark ML)
- Deep hands-on experience with implementation of SDLC best practices in complex IT projects
- Experience with automated data pipeline and workflow management tools (Airflow)
- Knowledge and experience in computer science disciplines such as data structures, algorithms, and software design patterns
- Hands-on experience in different data processing paradigms (batch, micro-batch, streaming)
- Deep understanding of MLOps concepts and best practices
- Experience with some of the MLOps related platform/technology such as AWS SageMaker, Azure ML, GCP Vertex AI / AI Platform, Databricks MLFlow, Kubeflow, Airflow, Argo Workflow, TensorFlow Extended (TFX), etc
- Production experience in integrating ML models into complex data-driven systems/IoT device/Mobile devices
- Experience with basic software engineering tools (CI/CD environments such as Jenkins or Buildkit, PyPi, Docker, Kubernetes)
- Experience with one of the infrastructures as a code (IoC) frameworks (Terraform/CDK TF, Ansible, AWS CloudFormation / AWS CDK)
What We Offer
- Extended Healthcare with Prescription Drugs, Dental and Vision Insurance (Company Paid)
- Life and AD&D Insurance (Company Paid)
- Employee Assistance Program (Company Paid)
- Unlimited access to LinkedIn learning solutions
- Long-Term Disability
- Registered Retirement Savings Plan (RRSP) with company match
- Paid Time Off
- Critical Illness Insurance
- Employee Discounts
