Senior ML Data Engineer

53 Minutes ago • 4-8 Years • Artificial Intelligence

Job Summary

Job Description

N-iX seeks a Senior ML Data Engineer to build and maintain a serverless ML-powered GraphQL stack. Responsibilities include partnering with stakeholders to define solutions, creating end-to-end ML solutions, supporting model deployment, manipulating large datasets, and providing operational support. The ideal candidate possesses expertise in building scalable real-time ML systems, Python microservices, SQL, modern ETL/stream processing frameworks (Airflow, DBT, Snowflake, Kafka, Kinesis), and ML tools (Scikit-Learn, TensorFlow, Keras, PyTorch). Cloud infrastructure experience is essential. The role involves close collaboration and innovation.
Must have:
  • Build scalable real-time ML systems
  • Expert Python & Microservices
  • SQL, data modeling, ETL (Airflow, DBT, Snowflake)
  • Stream processing (Kafka, Kinesis)
  • ML Ops experience
  • Scikit-Learn, TensorFlow/Keras/PyTorch
  • Cloud infrastructure
Perks:
  • Flexible working format
  • Competitive salary
  • Personalized career growth
  • Professional development tools
  • Education reimbursement
  • Corporate events

Job Details

N-iX is looking for a passionate and motivated Data ML Engineer to join our team.

Our customer is a technology company that powers one of the world's largest two-sided marketplaces for high-quality photos, illustrations, videos and music used by individuals, businesses, marketing agencies and media organizations of all sizes. In this role, you will be working with highly motivated and talented data scientists and engineers who are primarily focused on developing next generation AI/ML systems that transform the way people find content they enjoy.

Responsibilities:
■ Partner with product managers, data scientists and other technical stakeholders to understand requirements and collaborate on providing solutions at scale.
■ Create end-to-end machine learning solutions from start to finish, contribute to
complex machine learning operations and inference pipelines.
■ Build and maintain a modern serverless ML-powered GraphQL stack that will
support rapid iteration and drive delivery of AI-powered features.
■ Support development, productionalization and deployment of machine learning
models.
■ Manipulate large datasets quickly and efficiently in both relational and “big” data stores.
■ Day-to-day operational support of engineering infrastructure, products, and
services, including on-call routine.

Requirements:
■ Industry experience in building, deploying and maintaining high performing,
resilient, and scalable real-time machine learning systems.
■ Expert knowledge of Python and experience in building micro-services that can
scale effectively.
■ Knowledge of SQL, data modelling, and dimensionality modelling concepts
■ Familiarity with modern ETL stack (Airflow, DBT, Snowflake) and stream
processing frameworks (Kafka, Kinesis).
■ Good understanding of machine learning operation practices and procedures.
■ Familiarity with machine learning principles, hands-on experience with common machine learning tools like Scikit-Learn and deep learning frameworks likeTensorFlow, Keras, Torch/PyTorch
■ Experience with Cloud infrastructure provisioning and integration patterns
■ Be excited to be part of the team, have the ability to communicate clearly and
develop close working relations with other team members and stakeholders.
■ Ability to innovate and identify new approaches to improve current practices.

We offer:

  • Flexible working format - remote, office-based or flexible
  • A competitive salary and good compensation package
  • Personalized career growth
  • Professional development tools (mentorship program, tech talks and trainings, centers of excellence, and more)
  • Active tech communities with regular knowledge sharing
  • Education reimbursement
  • Memorable anniversary presents
  • Corporate events and team buildings
  • Other location-specific benefits

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