ML Engineer

ASSA ABLOY is a global leader in access solutions, dedicated to shaping the future of security and convenience. With a rich heritage spanning over 150 years, ASSA ABLOY has built a reputation for delivering innovative and reliable locking and access control solutions. Their diverse portfolio includes well-known brands like Yale, HID Global, and Mul-T-Lock, offering a comprehensive range of products and services to meet the unique needs of customers worldwide. From residential and commercial buildings to critical infrastructure and healthcare facilities, ASSA ABLOY's cutting-edge technologies ensure safety, security, and seamless user experiences. With a commitment to sustainability and customer satisfaction, ASSA ABLOY continues to drive advancements in access solutions for a safer and more connected world.

ML Engineer

Job Summary: We are seeking a skilled Machine Learning Engineer with 4-5 years of experience, particularly in leveraging Databricks for scalable data processing and machine learning model development. The ideal candidate will have a strong background in data science, a passion for solving complex problems, and the ability to collaborate effectively with cross-functional teams.

SUMMARY OF RESPONSIBILITIES

• Analyze, interpret, and model structured and unstructured data to address complex business challenges.

• Apply machine learning (ML) techniques, including supervised and unsupervised learning, reinforcement learning, and deep learning.

• Work with large datasets from various sources, such as databases, text, images, and other unstructured formats.

• Design, develop, and implement machine learning models and algorithms to solve business problems.

• Use Databricks to build and maintain data pipelines and workflows for data ingestion and processing.

• Implement Delta Lake in Databricks to enhance data storage, ensure consistency, and manage transactional data efficiently.

• Leverage Databricks MLflow for experiment tracking, model lifecycle management, and model versioning.

• Collaborate with data engineers and data scientists to optimize data architecture and ensure data/ML model quality.

• Perform exploratory data analysis to identify trends, patterns, and opportunities for model enhancement.

• Deploy and monitor machine learning models in production environments, ensuring high performance and reliability.

• Stay updated on industry trends and advancements in machine learning, particularly in large language models (LLMs) and big data technologies.

QUALIFICATIONS

To perform this job successfully, an individual must meet expectations of each essential duty. The requirements listed below are representative of the knowledge, skills and abilities required.

EDUCATION:

• Bachelor's degree Bachelor's degree in computer science/engineering 

Experience

• 4-5 years of experience in machine learning, data analysis, or a related role.

Preferred Qualifications:

• Strong proficiency in Python and experience with machine learning libraries (e.g., TensorFlow, PyTorch, Scikit-learn).

• Good understanding of LangChain, VectorDB, and LLMs

TECHNICAL KNOWLEDGE AND/OR ABILITIES:

• Hands-on experience with Databricks for data processing and machine learning workflows.

• Building and managing data pipelines using Databricks notebooks.

• Utilizing Delta Lake for data lake management and optimizing data storage.

• Working with Spark SQL for data querying and manipulation.

• In-depth knowledge of cloud services (AWS, Azure, or GCP) and their data offerings, such as:

• Storage solutions (e.g., S3, Azure Blob Storage, Google Cloud Storage).

• Data processing services (e.g., AWS Glue, Azure Data Factory).

• Machine learning services (e.g., AWS SageMaker, Azure ML).

• Experience with data visualization tools (e.g., Tableau, Power BI, Matplotlib).

• Solid understanding of statistical methods and data modeling techniques.

• Excellent problem-solving skills and ability to work in a fast-paced environment.

• Strong communication skills and ability to work collaboratively in a team.