Lead Machine Learning Engineer (relocation to Cyprus)

EPAM Systems — Entroncamento, PT
Published on

About the Role

We are looking for a Lead Machine Learning Engineer with a strong background in data science and software engineering to join us in Cyprus, working from our office in a flexible and hybrid work setup. As a Machine Learning Engineer, you will develop and deploy machine learning models, work with large datasets, and collaborate with cross-functional teams to solve business problems. This position is integral to one of our projects in the finance IT area, focusing on the integration component of the client's finance landscape. If you're ready to leverage your skills and perspective to make a significant impact, apply now and help us transform our data capabilities in the finance and insurance industries.

Responsibilities

  • Lead and contribute to ML pipeline design, development, and operating lifecycle based on best practices.
  • Be responsible for the transition of ML algorithms to production environment and integration with enterprise ecosystem.
  • Create infrastructure and architecture diagrams.
  • 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 the engineering team to optimize the performance of ML pipeline.
  • Constantly improve SDLC practices.
  • Establish and configure CI/CD/CT processes.
  • Allocate tasks to junior ML engineers and ensure task completion.
  • Provide capabilities for early detection of various drifts (data, concept, schema, etc.).

Requirements

  • 5+ years of experience as an ML engineer or Data Engineer in designing, building, and deploying production applications and data pipelines.
  • 1+ years of relevant leadership experience.
  • Strong knowledge and experience in Python development.
  • Deep understanding of Python ML ecosystem (PyTorch, TensorFlow, NumPy, Pandas, Sklearn, XGBoost, etc.).
  • Hands-on experience in the 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 the implementation of SDLC best practices in complex IT projects and with data processing paradigms.
  • Knowledge and experience in computer science disciplines such as data structures, algorithms, and software design patterns.
  • Experience with some of the MLOps related platforms/technologies such as AWS SageMaker, Azure ML, GCP Vertex AI/AI Platform, Databricks MLFlow, Kubeflow, Airflow, Argo Workflow, TensorFlow Extended (TFX), etc.
  • Experience with basic software engineering tools, e.g., git, CI/CD environment (such as Jenkins or Buildkite), PyPi, Docker, Kubernetes, unit testing, and general object-oriented design.
  • Strong communication and interpersonal skills to liaise with senior business stakeholders, clients, and team members.
  • Ability to work in a fast-paced, deadline-driven environment, mentor junior team members and provide technical leadership.
  • Fluent English language knowledge.

Company Culture and Benefits

We offer a range of benefits including private healthcare insurance, regular performance assessments, family-friendly initiatives, and corporate programs, including an Employee Referral Program with rewards. Learning and development opportunities include in-house training and coaching, professional certifications, and access to over 22,000 courses on LinkedIn Learning Solutions. *All benefits and perks are subject to certain eligibility requirements.

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