Lead Software Engineer (Operations Research)

About the job

Scope

• We are seeking an Optimization Specialist with a profound background in both classical
• optimization and advanced heuristic and metaheuristic methods. The ideal candidate will excel in
• formulating and solving various optimization problems (LP, MILP, combinatorial optimization,
• scheduling, etc.) and will be adept in applying innovative algorithms, including genetic algorithms,
• simulated annealing, tabu search, and particle swarm optimization, to achieve optimal solutions.
• This role is pivotal in driving operational efficiency and strategic decision-making through the
• application of sophisticated mathematical and statistical techniques.
• 
  

Our Current Technical Environment

• Software: Python 3.*
• Frameworks/Others: TensorFlow, PyTorch, BigQuery/Snowflake, Apache Beam, Apache Spark, Kubeflow, Dataflow, Databricks , Kubernetes, Kafka, Pub/Sub, and Flask.
• Application Architecture: Scalable, Resilient, Reactive, event driven, secure multi-tenant
• Microservices architecture.
• Cloud: Google Cloud and/or Azure
• 
  

What You'll Do

• Identify and model optimization problems across different business units, focusing on LP, MILP, combinatorial optimization, and scheduling.
• Design and implement robust optimization algorithms, including both classical methods and advanced heuristic and metaheuristic techniques such as genetic algorithms, simulated annealing, tabu search, and particle swarm optimization.
• Evaluate and select appropriate non-commercial (e.g., COIN-OR, SCIP) and commercial solvers (e.g., Gurobi, CPLEX) for specific problems, customizing and extending as necessary.
• Collaborate with stakeholders to translate business challenges into quantitative models, offering innovative solutions that leverage optimization techniques.
• Perform data analysis and statistical validation of models and solutions, ensuring accuracy
• and efficacy.
• Keep abreast of the latest developments in optimization and computational intelligence,
• incorporating these advancements into problem-solving strategies.
• Document and communicate methodologies, solutions, and impacts of optimization projects to a diverse audience, including technical reports and presentations.
• Collaborate with stakeholders and cross functional teams to understand business needs and translate them into technical requirements and architectural designs.
• Define the design, architectural and engineering patterns / standard for the team to follow.
• Involve actively in architecture and code reviews and provids feedback to ensure software quality and its compliance to architectural patterns and guidelines.
• Work closely with project managers, lead engineers, functional analysts, and other stakeholders to define project scope, priorities, estimates and timelines.
• Drive the adoption of cloud-native architectures and microservices-based solutions.
• Identify and mitigate technical risks and challenges throughout the software development
• lifecycle.
• Develop and/or contribute towards proof-of-concept work, as and when needed.
• Create and maintain documentation related to architecture, design, and other technical artifacts.
• Own the Non-functional requirements and outcomes like (but not limited to) Observability, Scalability, Reliability and Performance.
• Push the team towards better quality software by constructively pointing out opportunities to reduce complexity and to write cleaner code and more effective tests.
• Actively promote best practices
• Help other team members to come up with simpler, more robust, and more efficient designs and code.
• Identify root causes of issues and fixes those rather than their symptoms.
• Actively share knowledge in their field of expertise, e.g., by contributing to open source software projects, offering training sessions, holding conference presentations, etc.
• Empower, mentor, and grow less experienced team members, e.g., by sharing knowledge and providing hints so they come up with their own solutions.
• Design services to be self-healing and to offer self-service capabilities from the ground up to achieve minimum manual intervention.
• 
  

What We Are Looking For

• 5 to 8 years of experience in Operations Research.
• Master's or Ph.D. in Operations Research, Applied Mathematics, Statistics, Computer Science, Data Science, or a related field.
• Deep understanding of a wide range of optimization theories and methods, including LP, MILP, combinatorial optimization, scheduling, and especially heuristic and metaheuristic algorithms (genetic algorithms, simulated annealing, tabu search, particle swarmoptimization).
• Proficient in optimization modeling languages and tools (e.g., AMPL, Python with PuLP or Pyomo, MATLAB).
• Demonstrable experience with both non-commercial and commercial optimization solvers, with a keen ability to tailor solutions to complex problems.
• Strong statistical analysis skills, with proficiency in tools such as Python.
• Excellent problem-solving abilities, creativity in approach, and a track record of innovative solutions in optimization.
• Effective communication skills for presenting complex concepts to technical and non[1]technical audiences.