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SPD Technology

We create empowering tech solutions that drive clients' growth.

Engineering Manager, Applied AI – Machine Learning Engineering

Engineering ManagerEngineering ManagerFull TimeRemoteLeadTeam 501-1,000Since 2006Company SiteLinkedIn

Location

Ukraine

Posted

8 days ago

Salary

0

Seniority

Lead

Job Description

Engineering Manager, Applied AI – Machine Learning Engineering

SPD Technology

• Play a vital role in executing the company’s AI and machine learning initiatives • Focus on generating and delivering insights from PitchBook’s wealth of structured data and unstructured text • Design, develop, and maintain AI & ML models, solutions, architecture, and services • Provide strong technical direction and problem-solve complex technical challenges • Ensure high-quality, scalable solutions from the team • Oversee the end-to-end lifecycle of AI/ML data systems—from research and development to deployment and operationalization • Mentor team members and foster a culture of innovation and collaboration • Collaborate with cross-departmental stakeholders and ensure alignment with business goals • Drive impactful change in a fast-paced, dynamic environment

Job Requirements

  • M.S. in Computer Science, Data Science, Machine Learning, Software Engineering, or related
  • 7+ years in engineering or data science roles with a machine learning focus
  • 3+ years in an engineering leadership role with direct management responsibilities of at least 5 people
  • 3+ years hands-on coding and delivering large-scale ML models and systems as a Machine Learning Engineer or Data Scientist. Natural language processing (NLP) experience a must
  • Extensive experience with Python and associated ML libraries such as pandas, scikit-learn, keras, and PyTorch. Strong SQL knowledge is a must
  • Experience owning machine learning services that are provided 'as a service' to other teams as part of a large-scale distributed microservices architecture
  • Experience with data pipelines, data platforms, and data lake/warehouse technologies, such as Apache Kafka, Amazon SNS/SQS/Kinesis, Apache Airflow, Spark, AWS Glue, GCP Cloud Dataflow, Snowflake
  • Experience with containerization technologies, including Kubernetes and Docker, and understanding how to build cloud-scale delivery, including scalability, resiliency, and recoverability
  • Has successfully delivered on large technical initiatives from scoping to launch, with a strong metrics focus
  • Excellent communication skills, written and verbal
  • English — Upper Intermediate or higher; Ukrainian — fluent

Benefits

  • Flexible schedule with participation in team ceremonies and cross-functional collaboration
  • Performance and merit reviews
  • Personal development plans
  • Corporate library access
  • Public speaking support
  • Referral bonus program

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