Applied AI/ML Software Engineer

Location: Noida, India

Thales is a global technology leader trusted by governments, institutions, and enterprises to tackle their most demanding challenges. From quantum applications and artificial intelligence to cybersecurity and 6G innovation, our solutions empower critical decisions rooted in human intelligence. Operating at the forefront of aerospace and space, cybersecurity and digital identity, we're driven by a mission to build a future we can all trust.

Present in India since 1953, Thales is headquartered in Noida and has other operational offices and sites spread across Delhi, Gurugram, Bengaluru and Mumbai, among others. Over 2200 employees are working with Thales and its joint ventures in India. Since the beginning, Thales has been playing an essential role in India's growth story by sharing its technologies and expertise in Defence, Aerospace and Cyber & Digital sectors. Thales has two engineering competence centres in India - one in Noida focused on Cyber & Digital business, while the one in Bengaluru focuses on hardware, software and systems engineering capabilities for both the civil and defence sectors, serving global needs. The Group has also established an MRO (Maintenance, Repair & Overhaul) facility in Gurugram to provide comprehensive avionics maintenance and repair services to Indian airlines and support the growth of the local aviation industry. Position SummaryApplied AI/ML Engineer design, develop, and industrialize AI/ML solutions that improve customer engagement and operational efficiency across MCS. The role spans machine learning, data pipeline management, model deployment, generative and agentic AI solution development. Taking ideas from PoC/MVP to production in close partnership within MCS, with CDI CTO organization and relevant Thales entities. You will operate within a small, multidisciplinary engineering team, evaluating emerging technologies, maintaining a Tech Radar of risks/opportunities, and deliver evidence-driven solutions under real production platform constraints. Essential Functions / Key Areas of Responsibility

• Collaborate closely with stakeholders across product teams, marketing teams and engineering teams to define AI/ML use cases, translate business problems into AI/ML-powered solutions.
• Conduct Data Exploration and analysis to extract actionable insights from structure and unstructured data.
• Apply state-of-the-art ML/DL methods (supervised/unsupervised learning, deep networks) across diverse use cases (e.g., anomaly detection, predictive analysis, fraud detection).
• Implement end-to-end ML pipelines (data ingestion, preprocessing, training, evaluation, deployment, monitoring).
• Integrate ML models into production systems on-premises or Cloud platforms (e.g. AWS, GCP, …).
• Implement monitoring and logging to track model drift and performance using appropriate metrics.
• Build PoC/MVP using open/closed‑source generative AI, agentic AI frameworks to assess feasibility and potential impact, helping to de-risk the investment before committing to full-scale development.
• Fine-tune and adapt pre-trained models to business use case specific needs.
• Design and develop robust end-to-end AI solution, including backend services, scalable APIs, and integration with user-facing front-end, applying software engineering best practices (CI/CD, version control, automated testing,…)
• Document solution architecture, system design, integration flows, operation and best practices for reproducibility and knowledge sharing.
• Stay current with AI/ML research and industry trends to propose new techniques and tools.

Minimum Requirements: Skills, Experience & Education

• Master's or bachelor's degree in computer science, Computer Engineering, AI/Data disciplines or related field.
• Senior Profile with min 5 years of experience in delivering applied AI or ML solution, from PoC to solution industrialization.
• Proficiency in Python. Familiarity with other programming and scripting languages is a plus.
• Hands‑on with Data Science tools/practices (data prep, validation, evaluation) and open‑source ML/DL libraries.
• Familiarity with Generative AI open/close source, framework and workflows (fine‑tuning and/or RAG) or strong motivation to learn and apply quickly.
• Tooling: Git, Linux/UNIX & shell scripting, Docker / Docker Compose; basic cloud exposure (e.g., AWS).
• Experience with PyTorch, TensorFlow and knowledge of Spark/Hadoop or distributed data processing is a plus.

Preferred Qualifications

• Independent and analytical thinker, with proactive approach to problem solving.
• Able to work independently as well as working with cross-functional teams.
• Adept at switching between diverse technologies and tasks to meet evolving project needs.

Physical Demands:

• Highly autonomous
• Comfortable dealing with fast paced technology evolution and project uncertainties.

Special Position Requirements:

• Global mindset to foster strong working relationships with colleagues worldwide. Flexible and willing to adapt working hours on occasion when necessary.

At Thales, we're committed to fostering a workplace where respect, trust, collaboration, and passion drive everything we do. Here, you'll feel empowered to bring your best self, thrive in a supportive culture, and love the work you do. Join us, and be part of a team reimagining technology to create solutions that truly make a difference – for a safer, greener, and more inclusive world.

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