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  • All offersWrocławDataSenior Machine Learning Engineer
    Senior Machine Learning Engineer
    Data
    Avenga

    Senior Machine Learning Engineer

    Avenga
    Wrocław
    Type of work
    Full-time
    Experience
    Senior
    Employment Type
    B2B
    Operating mode
    Remote
    Avenga

    Avenga

    We are a team of IT and digital transformation experts. Strategic consulting, customer experience service, software development, and outsourcing of top-class IT specialists is what we do (and more!).

    Company profile

    Tech stack

      Machine Learning

      advanced

      SQL

      advanced

      NoSQL

      advanced

      Cloud solution

      regular

      Big Data

      regular

      NLP

      nice to have

      LLM

      nice to have

      Docker

      nice to have

      TensorFlow

      nice to have

      Kubernetes

      nice to have

    Job description

    Online interview

    Senior Machine Learning Engineer, Generative AI Applications


    FTE: 1

    Duration: 6 months

    Working hours: 8 hours with so-called overlap from 16:00 -20:00 CET.

    Experience: senior

    English: B2/C1/C2

    Remote work: YES

    Recruitment process: Technical verification (1h) and Meeting with future manager


    Position Description

    As a Machine Learning Engineer, you will collaborate with data scientists, product managers, and data engineers to operationalize machine learning models in production and manage the lifecycle of artificial intelligence algorithms on a variety of domains. You will develop and deploy novel approaches to optimize existing machine learning systems to maximize their business value.


    Duties and Responsibilities:

    • Architect, build, maintain, and improve new and existing suite of algorithms and their underlying systems.
    • Automate machine learning pipelines and monitor and optimize machine learning solutions.
    • Implement end-to-end solutions for batch and real-time algorithms along with requisite tooling around monitoring, logging, automated testing, performance tuning, and A/B testing.
    • Use your entrepreneurial spirit to identify new opportunities to optimize business processes, improve consumer experiences, and prototype solutions to demonstrate value.
    • Work closely with data scientists and analysts to create and deploy new product features online and in mobile apps.
    • Establish scalable, efficient, automated processes for data analyses, model development, validation and implementation.
    • Write efficient and well-organized software to ship products in an iterative, continual-release environment.
    • Contribute to and promote good software engineering practices across the team.
    • Mentor and educate team members to adopt best practices in writing and maintaining production machine learning code.
    • Actively contribute to and re-use community best practices.
    • Monitor, debug, track, and resolve production issues.
    • Work with project managers to ensure that projects proceed on time and on budget.
    • Collaborate with Technical Product Managers to ensure proper tracking of algorithmic performance KPIs and prioritize performance improvements based on effort and impact. Complete other responsibilities as assigned.


    Basic Qualifications

    • Minimum of seven years’ post-secondary education or relevant work experience


    Other Required Qualifications:

    • Minimum of seven years’ post-secondary education or relevant work experience Bachelor's degree in mathematics, physics, computer science, engineering, statistics, or an equivalent technical discipline.
    • Minimum of five years’ software development experience with Python and SQL.
    • Minimum of three years’ experience in developing and deploying machine learning systems into production in a cloud environment.
    • Minimum of two years’ experience testing, maintaining, or launching software products and minimum of one year of experience with software design and architecture.
    • Experience working with a variety of relational SQL and NoSQL databases, big data tools: Hadoop, Spark, Kafka; a Linux environment; and at least one cloud provider solution (AWS, GCP, Azure).
    • Knowledge of data pipeline and workflow management tools.
    • Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.


    Other Preferred Qualifications:

    • Experience with neural networks, deep learning, and reinforcement learning, using frameworks such as TensorFlow.
    • Experience with Natural Language Processing (NLP), Large Language Models (LLMs), and/or Recommendation Engines.
    • Relevant working experience with Docker and Kubernetes.