Data & Machine Learning Engineer

Data & Machine Learning Engineer

Are you a seasoned data and machine learning expert with a passion for building enterprise-grade data pipelines and machine learning infrastructure? Do you thrive in mentoring junior engineers while tackling complex technical challenges? If so, we want you on our team!

We offer:

Maersk, the world's largest shipping company, is transforming into an industrial digital giant that enables global trade with its land, sea and port assets. We are the digital and software development organization that builds products in the areas of predictive science (forecasting, customer and market analytics), optimization and IoT. This position offers the opportunity to build your engineering career in a data and analytics intensive environment, delivering work that has direct and significant impact on the success of our company. Global data analytics delivers internal apps to grow revenue and optimize costs across Maersk's Transport & Logistics companies. We practice agile development in teams empowered to deliver products end-to-end, for which data and analytics are crucial assets. This is an extremely exciting time to join a fast paced, growing and dynamic team that solves some of the toughest problems in the industry and builds the future of trade & logistics. We are an open-minded, friendly and supportive group who strive for excellence together A.P. Moller - Maersk maintains a strong focus on career development, and strong team members regularly have broad possibilities to expand their skill set and impact in an environment characterized by change and continuous progress.

Job location: Bangalore, India

What we are looking for:

We are seeking a highly motivated Data & Machine Learning Engineer to join our growing team. In this role, you will take ownership of designing, developing, and implementing robust data pipelines and machine learning infrastructure on leading cloud platforms.

You will not only excel in technical execution but also provide guidance and mentorship to junior engineers, fostering a collaborative and high-performing team environment.

Responsibilities:

• Spearhead the design, development, and implementation of scalable and secure data pipelines on leading cloud platforms (e.g., AWS, GCP, Azure) using services like Data Factory, Databricks, Synapse Analytics, or similar offerings.

• Architect and implement data solutions that meet the evolving needs of the business and machine learning initiatives.

• Develop and maintain robust data processing solutions using big data technologies like Spark, Python, and SQL.

• Optimize data pipelines for performance, efficiency, and cost-effectiveness.

• Partner with data scientists to define data requirements for machine learning models and ensure high-quality data for training and analysis.

• Select, implement, and compare different machine learning algorithms for specific tasks, considering factors like model complexity, interpretability, and computational efficiency.

• Develop, train, and evaluate machine learning models using relevant libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn)

• Conduct exploratory data analysis (EDA) and feature engineering to identify and extract relevant features for model training.

• Conduct hyper-parameter tuning and feature engineering to optimize model performance.

• Automate model retraining pipelines to ensure models stay up to date with changes in the underlying data distribution. Deployment of machine learning algorithms/models.

• Proactively monitor and troubleshoot data pipelines to identify and resolve issues before they impact operations.

• Spearhead and mentor junior engineers, fostering their technical growth and development.

• Contribute to the development and documentation of technical standards and best practices.

Qualifications:

• 5+ years of experience in data engineering with a strong focus on cloud platforms. Awareness about azure services is a plus.

• Proven track record of designing, developing, and deploying complex data pipelines at scale.

• In-depth expertise in data ingestion, transformation, and cleansing techniques.

• Solid understanding of machine learning concepts and frameworks.

2+ years of experience applying machine learning algorithm to real-world problems (required).

• Mastery of programming languages like Python and SQL, with experience in big data frameworks like Spark (a plus).

• Experience with data warehousing, data lakes, and containerization technologies (Docker, Kubernetes) (a plus).

• Experience with DevOps fundamentals and practices for continuous integration and delivery

(CI/CD).

• Excellent communication, collaboration, and problem-solving skills.

Maersk is committed to a diverse and inclusive workplace, and we embrace different styles of thinking. Maersk is an equal opportunities employer and welcomes applicants without regard to race, colour, gender, sex, age, religion, creed, national origin, ancestry, citizenship, marital status, sexual orientation, physical or mental disability, medical condition, pregnancy or parental leave, veteran status, gender identity, genetic information, or any other characteristic protected by applicable law. We will consider qualified applicants with criminal histories in a manner consistent with all legal requirements.

We are happy to support your need for any adjustments during the application and hiring process. If you need special assistance or an accommodation to use our website, apply for a position, or to perform a job, please contact us by emailing accommodationrequests@maersk.com.