Sr ML Engineer

3 weeks ago

Chennai, India ASSA ABLOY Full time

Sr 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.

We are seeking a talented and experienced Machine Learning Engineer with a strong background in developing and implementing machine learning solutions. The ideal candidate will have a minimum of 2 years of real-time experience, demonstrating expertise in machine learning algorithms, model deployment, and a solid understanding of cloud platforms, particularly Azure.

SUMMARY OF RESPONSIBILITIES

• Develop, implement, and optimize machine learning models to address business challenges and improve processes.
• Collaborate with cross-functional teams to gather requirements, understand business objectives, and translate them into actionable ML solutions.
• Stay updated with the latest advancements in traditional AI and Gen AI, machine learning and contribute innovative ideas to enhance our data science capabilities.
• Build, train, and deploy ML models at scale, ensuring efficient integration into production environments.
• Work closely with data engineers to pre-process and clean data for model training and validation.
• Evaluate and select appropriate tools, technologies, and frameworks for machine learning development in an Azure environment.

KEY QUALIFICATIONS

• Minimum of 2 years of real-time experience as a Machine Learning Engineer.
• Solid understanding of machine learning algorithms, including supervised and unsupervised learning techniques.
• Proficient in programming languages such as Python, with experience in libraries like OpenCV, TensorFlow, PyTorch, or Scikit-learn.
• Hands-on experience with Azure Machine Learning services and tools.
• Strong knowledge of cloud platforms, particularly Azure, and experience in deploying machine learning models to cloud environments.
• Familiarity with best practices in model evaluation, validation, and monitoring in production environments.
• Experience with data pre-processing, feature engineering, and working with large datasets.
• Excellent problem-solving skills and a proactive approach to addressing challenges.
• Good to have: Familiarity with Business Intelligence (BI) technologies such as Power BI, SSIS, etc.

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 or master’s degree in computer science, Machine Learning, Data Science, or related field.

EXPERIENCE:

5 Years IT with 2 years ML

We are the ASSA ABLOY Group
Our people have made us the global leader in access solutions. In return, we open doors for them wherever they go. With nearly 52,000 colleagues in more than 70 different countries, we help billions of people experience a more open world. Our innovations make all sorts of spaces – physical and virtual – safer, more secure, and easier to access.

As an employer, we value results – not titles, or backgrounds. We empower our people to build their career around their aspirations and our ambitions – supporting them with regular feedback, training, and development opportunities. Our colleagues think broadly about where they can make the most impact, and we encourage them to grow their role locally, regionally, or even internationally.

As we welcome new people on board, it’s important to us to have diverse, inclusive teams, and we value different perspectives and experiences.

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