AI/ML Engineer - (Network Optimization)

Reposted 16 Days Ago
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560025, Shanti Nagar, Karnataka, IND
In-Office
Mid level
Logistics • Transportation
The Role
Looking for an AI/ML Engineer to build and deploy forecasting models, develop ML models for optimization, and collaborate with business teams to translate problems into ML solutions.
Summary Generated by Built In

Maersk Ground Freight (MGF) is the go-to-market brand for Maersk’s Middle Mile business. We are at the forefront of developing cutting-edge technologies to improve the customer’s experience with personalized and automated end-to-end digital journeys that enable Maersk customers to access standardized products and services seamlessly.

MGF offers transportation services like FTL (Full Truckload), LTL (Less Than Truckload), Brokerage, Cross-border trucking, Groupage, Sortation hubs, connecting Maersk or Customer warehouses or Depots or Cross-dock/Consolidation/Deconsolidation facilities through a robust network led by best-in-class operations and technology. This integrated network services multi-channels like B2B, B2C, Direct to Store, Dropship, Returns, and more, leveraging asset-based, asset-light, and non-asset models.

With a presence in 100+ countries, we are improving life for all by integrating the world. If you are passionate about leading and building a global business, taking on the challenges on behalf of our Customers, and working with a fantastic group of colleagues, reach out to us.

Job Title: AI/ML Engineer- Network Optimization

Key Responsibilities

  • Develop and implement optimization models for transportation, network design, capacity planning, and inventory optimization.
  • Apply Operations Research techniques to solve complex supply chain and logistics problems.
  • Build mathematical models for cost, service, and capacity optimization.
  • Analyze network scenarios and recommend improvements.
  • Collaborate with business stakeholders to translate operational challenges into optimization solutions.

Required Skills

  • Strong foundation in Operations Research.
  • Linear Programming (LP).
  • Mixed Integer Linear Programming (MILP/MIP).
  • Network Flow Optimization.
  • Transportation and Logistics Optimization.
  • Python.
  • SQL.
  • Optimization tools such as:
  • OR-Tools
  • Gurobi
  • CPLEX
  • Pyomo
  • PuLP

Preferred Skills

  • Supply Chain Network Design.
  • Simulation Modeling.
  • Forecasting knowledge.

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  [email protected]

Skills Required

  • Hands-on experience in ML model development & deployment
  • Strong background in time-series forecasting
  • Experience working with large datasets in cloud environments
  • Exposure to logistics / supply chain analytics
  • Experience with Azure (Databricks, Azure ML, Data Factory, Synapse)
  • Experience with Python (pandas, PySpark)
  • Experience with SQL, Power BI
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The Company
HQ: Copenhagen
58,338 Employees

What We Do

A.P. Moller - Maersk is an integrated transport and logistics company; going all the way, together, for our customers and society. ALL THE WAY is our commitment to connect the world so that everyone has both the possibility and the ability to trade, grow and thrive. The company employs roughly 110.000 employees across operations in 130 countries.

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