AI/Machine Learning Engineer with Databricks

EPAM Systems; Turkey; On-site; TRY 3,949,000 - 6,417,000; Full time

Benefits offered by this job

Private health insurance

Extra leave days

Referral bonuses

IT Equipment

English courses

Job summary

EPAM Systems seeks a hands-on AI/ML Engineer to design and deploy optimized feature engineering and real-time inference pipelines, including Spark Streaming and batch training. You will work with Databricks, PySpark, Python, and SQL to process structured and unstructured data at scale and ensure low-latency deployment in production.

Applicants should have 3+ years of experience, strong knowledge of Spark Streaming, and English at B2 level or higher, with a track record of production-grade ML

Qualifications

• 3+ years of experience building, deploying, and operating offline and online feature engineering pipelines.
• Strong experience with model training and real-time inferencing pipelines.
• Hands-on expertise in Databricks, Spark/PySpark, Python, and SQL.
• Experience processing large-scale unstructured data.
• Strong knowledge of Spark Streaming.
• Experience with real-time feature generation and low-latency model inference.
• Experience building and supporting batch pipelines for model training and retraining.
• Proven track record of running production-grade ML systems.
• English proficiency at B2 level or higher.

Responsibilities

• Design and optimize feature engineering pipelines for both batch and real-time workloads.
• Build, deploy, and maintain scalable model training and inference pipelines.
• Process structured and unstructured data at scale.
• Develop streaming solutions using Spark Streaming.
• Enable real-time feature generation and model serving.
• Ensure reliability, scalability, and performance of ML solutions in production.

Skills

Databricks

Spark/PySpark

Python

SQL

Spark Streaming

Tools

MLflow

AWS

Job description

We are looking for a hands-on AI/Machine Learning Engineer with proven experience deploying and running optimized feature engineering (offline and online), model training, and inference pipelines. Experience with unstructured data processing and Spark Streaming is a must. Real-time feature generation and inference are required for this project, along with batch pipelines for model training.

Responsibilities

• Design and optimize feature engineering pipelines for both batch and real-time workloads
• Build, deploy, and maintain scalable model training and inference pipelines
• Process structured and unstructured data at scale
• Develop streaming solutions using Spark Streaming
• Enable real-time feature generation and model serving
• Ensure reliability, scalability, and performance of ML solutions in production

Requirements

• 3+ years of experience building, deploying, and operating offline and online feature engineering pipelines
• Strong experience with model training and real-time inferencing pipelines
• Hands-on expertise in Databricks, Spark/PySpark, Python, and SQL
• Experience processing large-scale unstructured data
• Strong knowledge of Spark Streaming
• Experience with real-time feature generation and low-latency model inference
• Experience building and supporting batch pipelines for model training and retraining
• Proven track record of running production-grade ML systems
• English proficiency at B2 level or higher

Nice to have

• Experience with MLflow and MLOps
• Experience with AWS
• Background in Customer Analytics, Recommendation Systems, or Retail

We offer

• CONTINUOUS UPSKILLING, LEARNING & DEVELOPMENT
  • Diversity of tasks and projects
  • Assessment center for objective review of competency level
  • Personal development plan
  • Mentoring programs and leadership development
  • Certification and professional development support
  • Access to learning platforms including more than 2,500 internal courses
  • English courses taught by certified teachers
• CORPORATE BENEFITS
  • Extra leave days
  • Referral bonuses
• COMPENSATION PACKAGE
  • Competitive compensation paid in USD
  • Regular salary and performance reviews
• MEDICAL & HEALTHCARE
  • Private health insurance
  • Well-being events
• WORKING ENVIRONMENT
  • Recreation areas and kitchens
  • Tea, coffee and snacks
  • Sports equipment and game consoles
  • IT Equipment
  • Microsoft’s Software Assurance Home Use Program (HUP)

Please note that our Talent Attraction Team reviews applications and CVs submitted in English. EPAM is global leader in AI transformation engineering and integrated consulting, serving Forbes Global 2000 companies and ambitious startups. With over thirty years of expertise in custom software, product and platform engineering, we empower our clients to become AI-Native enterprises, driving measurable value from innovation and digital investments.