Data Infrastructure & ML Engineer (Hybrid Role)

Axcelis Technologies, Inc.; Beverly (MA); Hybrid; USD 122,133 - 183,199; Full time

Benefits offered by this job

Comprehensive benefits package

Eligibility in Axcelis Team Incentive bonus plan

Job summary

Axcelis Technologies, Inc. is seeking a Senior Data Infrastructure & Machine Learning Engineer to design scalable data systems and pipelines for advanced analytics. This hybrid role emphasizes data pipeline engineering and Python-based processing, requiring strong database management skills.

The ideal candidate will have at least 5 years of experience and a degree in Computer Science or Engineering, along with expertise in building data pipelines and strong proficiency in Python. A comprehensive benefits package is offered, along with a competitive salary range of $122,133.07 - $183,199.61 based on location and experience.

Qualifications

• 5+ years of experience in database design and SQL-based systems.
• Strong proficiency in Python for data processing.
• Hands-on experience with distributed systems, partitioning, and sharding.

Responsibilities

• Design and build end-to-end data pipelines (ETL/ELT) for data ingestion.
• Manage scalable database schemas and optimize queries.
• Develop data processing workflows using Python and automate data workflows.

Skills

Database design

Python programming

Data pipeline engineering

Experience with JSON

Education

Bachelor’s or Master’s degree in Computer Science or Engineering

Tools

Pandas

NumPy

Kafka

Job description

Role Summary

We are seeking a Senior Data Infrastructure & Machine Learning Engineer to design and implement scalable data systems and pipelines that support advanced analytics and machine learning workflows. This is a hybrid role where the primary focus is on data pipeline engineering and Python-based data processing, supported by strong database design and management expertise.

Role Focus (Approximate Split)

• Data Pipeline Engineering & Data Flow (Critical): ~50%
• Python & Machine Learning Data Processing: ~30%
• Database Design & Management: ~20%

Key Responsibilities

1. Data Pipeline Engineering (Primary Responsibility) Design and build end-to-end data pipelines (ETL/ELT) for ingesting, processing, and transforming data. Handle multiple data sources including:
   • Tool-generated logs (e.g., AT log files)
   • JSON and semi-structured data
   Ensure full data traceability, enabling backward tracking of all data points. Implement validation, monitoring, and error handling to ensure data quality and reliability.
2. Database Design & Data Architecture Design and manage scalable database schemas. Support both single-node and distributed database environments. Implement tablespaces, partitioning, and sharding strategies to ensure performance and scalability. Optimize queries and maintain high performance for large-scale datasets.
3. Python-Based Data Processing & Analytics Develop data processing workflows using Python. Work extensively with dataframes for transformation and analysis. Utilize libraries such as Pandas, NumPy for data manipulation, Plotly (or similar) for visualization and exploratory analysis. Automate data workflows and integrate them into pipelines.
4. Machine Learning Data Enablement Prepare and transform datasets for machine learning models. Collaborate with data scientists and engineers to support model training and deployment workflows. Enable scalable data foundations for AI/ML integration into production systems.

Required Qualifications

• Bachelor’s or Master’s degree in Computer Science, Engineering, or related field with 5+ years of experience.
• Strong experience in database design and SQL-based systems.
• Hands‑on experience with distributed systems, partitioning, and sharding.
• Proven experience building data pipelines (ETL/ELT).
• Strong proficiency in Python for data processing.
• Experience working with log-based and semi-structured data (e.g., JSON).
• Understanding of data traceability, validation, and governance.

Preferred Qualifications

• Experience with time‑series or log analytics systems.
• Exposure to real‑time/streaming architectures (e.g., Kafka).
• Experience with cloud platforms (Azure, AWS, or GCP).
• Familiarity with machine learning workflows and lifecycle.
• Domain experience in semiconductor or high-throughput systems (nice to have).

Key Competencies

• Strong problem‑solving and analytical skills.
• Ability to design production‑grade, scalable systems.
• Focus on data integrity, performance, and reliability.
• Effective collaboration across engineering and data teams.
• Clear communication and documentation.

EQUAL OPPORTUNITY STATEMENT

It is the policy of Axcelis to provide equal opportunity in all areas of employment for all persons free from discrimination based on race, sex, religion, age, color, national origin, disability status, medical condition (including pregnancy), veteran status, sexual orientation, marital status, or any other characteristic protected by federal, state or local law. Axcelis will provide reasonable accommodation necessary to enable a disabled candidate or employee to perform the essential functions of the position, unless the accommodation would create an undue hardship for the Company.

Salary & Benefits

U.S. BASE SALARY RANGE $122,133.07 - $183,199.61. This base salary range reflects the typical compensation for this role across U.S. locations. Our salary ranges are determined by role and level; individual pay is determined based on multiple factors, including job‑related skills, experience, relevant education or training, work location, and internal equity. The range provides the opportunity for growth and progression as you develop within the role. Base pay is one part of our U.S. total compensation package which includes eligibility in the Axcelis Team Incentive bonus plan, and comprehensive benefits package (for regular employees working 20+ hours a week).