Senior/Lead Machine Learning Engineer
Ramboll
Lead AI engineer shaping scalable, responsible ML/LLM systems for Ramboll's digital platform.
24 days ago ago
Expert & Leadership (13+ years), Experienced (8-12 years)
Full Time
Gurugram, Haryana, India
Office Full-Time
Company Size
18,000 Employees
Service Specialisms
Engineering and Design
Management Consulting
Mechanical and Electrical Engineering
Project Management
Construction Management
Master Planning
Environmental and Nature‑based Solutions
Smart Mobility
Sector Specialisms
Energy
Infrastructure
Industrial
Buildings
Transport
Water Resources
Utilities
Government
Role
What you would be doing
automation
metrics
ai architecture
ml ops
evaluation
ci/cd
- Develop and optimize automated training, deployment, and monitoring workflows across environments.
- Establish metrics and dashboards to monitor quality, latency, sustainability metrics, and cost, identifying and implementing improvements for better outcomes
- Design and maintain AI and agentic architectures that enable autonomous reasoning, decision support, and knowledge integration across Ramboll’s digital platforms.
- Lead initiatives that embed intelligent automation and reasoning capabilities into engineering workflows.
- Architect and deliver scalable ML, LLM, and multi-agent systems that integrate structured and unstructured data sources.
- Mentor ML Engineers and Developers, fostering growth in system design, evaluation frameworks, and AI lifecycle management.
- Drive adoption of AI observability practices for continuous improvement and compliance.
- Contribute to global AI capability building through knowledge sharing, reusable frameworks, and cross-Pod collaboration.
- Lead by example in implementing sustainable, cost-efficient, and transparent ML operations.
- Design and apply robust evaluation frameworks to measure model and agent performance, transparency, and bias.
- Partner with Product Architects, Data Engineers, and Chapter Leads to operationalize AI and agentic architectures in digital products.
- Define design principles, standards, and guardrails to ensure technical excellence, reproducibility, and ethical AI development.
- Integrate orchestration principles for multi-agent and retrieval-augmented (RAG) pipelines into CI/CD processes, ensuring scalable, reliable AI delivery.
What you bring
langchain
python
mlops
llms
bachelor's
mentoring
- Agentic AI & RAG Systems: Experience building multi-agent workflows, reasoning graphs, and retrieval-augmented generation pipelines using modern frameworks such as LangChain, LangGraph, or Semantic Kernel.
- Demonstrated mentoring and technical coaching experience.
- Ability to define and communicate AI and agentic architecture direction aligned with Ramboll’s strategic goals.
- Clear communicator who builds trust and drives collaboration across teams.
- AI & Agentic Architecture: Experience designing system architectures for agent-based and knowledge-integrated AI applications.
- Programming & Tools: Proficiency in Python and frameworks such as PyTorch, TensorFlow, scikit-learn, or Hugging Face.
- Evaluation & Observability: Skilled in model and agent evaluation, benchmarking, and feedback tracking using enterprise frameworks (e.g., LangFuse, MLflow).
- Governance: Understanding of Responsible AI principles, model documentation, and enterprise compliance practices.
- ML/LLM Engineering: Advanced expertise in model development, orchestration, and lifecycle management.
- Minimum 5 years of experience in machine-learning or AI system development.
- Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
- At least 2 years in a senior or lead capacity within agile, cross-functional teams.
- Proven track record developing and deploying LLM-based, agentic, or ML-driven systems at production scale.
- MLOps & Automation: Experience with model versioning, deployment, and automated CI/CD pipelines in cloud environments.
- Large Language Models (LLMs): In-depth experience with modern LLMs such as GPT, Claude, Gemini, Llama, Falcon, or Mistral.
- Cloud & Infrastructure: Experience with Azure, AWS, or GCP; familiarity with containerization (Docker, Kubernetes) a plus.
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Interview process
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Company
Overview
35 Countries
Global Presence
The company has expanded its operations to over 35 countries worldwide, showcasing its international reach and influence.
Revenue 2022
Annual Revenue
The company achieved a revenue of DKK 16 billion in 2022, reflecting its strong financial performance.
Net Income 2022
Profitability
With a net income of DKK 937 million in 2022, the company demonstrated consistent profitability and growth.
- Evolved from a Nordic firm into a multinational player with offices in over 35 countries.
- Renowned for landmark infrastructure: Öresund Bridge, Great Belt Bridge, Copenhagen Opera House, Tate Modern extension.
- Offers multidisciplinary services spanning structural design, geotechnical, HVAC, traffic, environmental and digital engineering.
- Typical projects include urban transport systems, cultural icons, energy plants, water infrastructure and environmental assessments.
- Unusual engagements: projects in Antarctica and immersive tunnels like Fehmarn Belt.
- Owned by an independent foundation, enabling long-term investment in innovation and reinvestment into the firm.
- Focus on cultivating meaningful insights and achieving high standards in all endeavors.
- Commitment to ethical practices and understanding customers' and team members' needs.
- Encouraging collaborative environments where everyone feels confident to contribute ideas and take ownership of their roles.
- Create a positive work atmosphere where employees can engage with their work enthusiastically.
90% reduction
GHG Emissions Target
Achieve a 90% reduction in greenhouse gas emissions across scopes 1, 2, and 3 by 2040, with the remaining 10% neutralized through carbon removal.
53.9% reduction
Scope 1 & 2 Emissions
Aim to reduce scope 1 and 2 emissions by 53.9% by 2030.
70% suppliers
Science‑Based Targets
Ensure that 70% of suppliers (by emissions) have science‑based targets by 2028.
40% EVs
Electric Vehicle Fleets
Over 40% of company fleets in multiple European countries are electric vehicles.
- Approved by Science Based Targets initiative (May 2024)
- Exiting oil & gas exploration before end‑2025; redeploying expertise to renewables
- ISO 14001‑certified environmental management system
37% Women Workforce
Global Workforce Demographics
The company has 37% women representation across the total workforce as of 2023.
32% Women Top Management
Top Management Gender Representation
32% of top management roles (including GEB, leadership, and global function heads) are held by women.
92% Survey Participation
Employee Engagement Survey
The annual ESES employee survey had a 92% participation rate among employees.
4.2/5 Satisfaction
Employee Satisfaction Score
Employees scored the company a 4.2/5 satisfaction rating in the 2023 ESES survey.
- Aim to achieve ~40% women representation in the workforce by the end of the strategy period.
- Women in new hires: 40% globally.
- Women in senior leadership: 27–32% (2023–2024).
- Aspirational EDI goals include building a culture of inclusion and belonging, ensuring balanced gender representation, and embedding diversity and equity in people processes.
- Key EDI initiatives include Women in STEM mentorship, STEM school partnerships, menopause and safety workshops, Girls’ Day in Science, and strategic partnerships with organizations like NSBE and HunterWiSE.
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