Machine Learning Engineer

Industrial Digital Solutions is at the forefront of developing innovative software solutions for the industrial sector. We are expanding our Digital Factory Suite (DFS) portfolio to include cutting-edge cloud-based predictive maintenance and other applications that address critical customer needs. Our goal is to empower our customers with insights into future trends, equipment wear, abnormal situations, and potential safety hazards, ultimately improving product quality and driving subscription growth.

A Day in Your Life at MKS:

As a Machine Learning Engineer, you will be instrumental in designing, developing, and deploying robust and scalable machine learning models for our innovative DFS solutions. You will be responsible for understanding requirements, collecting and preparing data, building and evaluating ML models, and collaborating closely with cross-functional teams to integrate these models into production systems. Additionally, you will be expected to contribute to the overall ML strategy, research new algorithms, and improve existing models. In this role, you will report to the Lead of DFS Development Team.

You Will Make an Impact By:

ML Model Development: Design, develop, and implement machine learning models based on requirements and real-world data, focusing on predictive maintenance and anomaly detection.

Data Preprocessing and Feature Engineering: Perform thorough data collection, cleaning, transformation, and feature engineering to prepare datasets for model training and evaluation.

Model Training and Evaluation: Train and optimize machine learning models, utilizing various algorithms and frameworks. Evaluate model performance using appropriate metrics and techniques.

Model Deployment and Integration: Deploy ML models into production environments and ensure seamless integration with existing systems and applications.

Model Monitoring and Maintenance: Implement monitoring strategies for deployed models to track performance, detect drift, and ensure ongoing reliability. Maintain and update models as needed.

Algorithm Research and Selection: Stay up-to-date with the latest advancements in machine learning research and evaluate new algorithms and techniques for potential application within DFS solutions.

Collaboration: Work closely with data scientists, software developers, product managers, and other stakeholders to understand requirements, provide technical insights, and ensure the successful delivery of ML-powered products.

MLOps Involvement: Collaborate with MLOps engineers to streamline the ML lifecycle, including continuous integration, continuous delivery, and automated testing of ML models.

Performance Optimization: Identify and implement optimizations for ML models and pipelines to improve efficiency, scalability, and resource utilization.

Knowledge Sharing: Stay up to date with the latest ML methodologies, tools, and best practices, and share knowledge with the team.

What You Bring to the Team:

3+ years of experience in machine learning engineering or a related field with a strong foundation in model development, deployment, and MLOps, and an interest in cutting-edge ML research.

Bachelor’s or Master’s degree in computer science, Machine Learning, Statistics, or a related quantitative field, or equivalent experience.

Proven experience as a Machine Learning Engineer with a focus on practical model development and deployment.

Demonstrated ability to effectively design, implement, and evaluate machine learning solutions.

A proactive attitude and a willingness to learn and contribute to advanced ML initiatives and research.

Machine Learning Expertise: Proven ability to design, develop, and deploy machine learning models for various applications, with a focus on predictive analytics.

Programming Languages: Strong proficiency in programming languages commonly used in ML (e.g., Python, R). Experience with C++ is a plus.

ML Frameworks: Experience with popular machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

Data Handling: Strong understanding of data manipulation and analysis techniques, including SQL and NoSQL databases.

Analytical and Problem-Solving Skills: Ability to analyze complex problems, identify appropriate ML solutions, and troubleshoot model-related issues effectively.

English Proficiency: Ability to read and write technical documentation and communicate effectively with colleagues in English.

Interest in MLOps: A strong desire to learn and contribute to MLOps practices and infrastructure.

Preferred Skills:

Experience with cloud platforms (e.g., AWS, Azure, Google Cloud) for ML deployment.

Familiarity with containerization technologies (e.g., Docker, Kubernetes).

Experience with big data technologies (e.g., Spark, Hadoop).

Familiarity with Agile development methodologies (e.g., Scrum, Kanban).

Domain Knowledge: Familiarity with industrial automation and/or predictive maintenance applications.

Polish/Russian language skills.

We can't wait for your application !

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Globally, our policy is to recruit individuals from wide and diverse backgrounds. However, certain positions require access to controlled goods and technologies subject to the International Traffic in Arms Regulations (ITAR) or Export Administration Regulations (EAR). Applicants for these positions may need to be “U.S. persons.” “U.S. persons” are generally defined as U.S. citizens, noncitizen nationals, lawful permanent residents (or, green card holders), individuals granted asylum, and individuals admitted as refugees.

MKS Instruments, Inc. and its affiliates and subsidiaries (“MKS”) is an affirmative action and equal opportunity employer: diverse candidates are encouraged to apply. We win as a team and are committed to recruiting and hiring qualified applicants regardless of race, color, national origin, sex (including pregnancy and pregnancy-related conditions), religion, age, ancestry, physical or mental disability or handicap, marital status, membership in the uniformed services, veteran status, sexual orientation, gender identity or expression, genetic information, or any other category protected by applicable law. Hiring decisions are based on merit, qualifications and business needs. We conduct background checks and drug screens, in accordance with applicable law and company policies.  MKS is generally only hiring candidates who reside in states where we are registered to do business.

MKS is committed to working with and providing reasonable accommodations to qualified individuals with disabilities. If you need a reasonable accommodation during the application or interview process due to a disability, please contact us at: accommodationsatMKS@mksinst.com .

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