Experience:

• 3+ years of professional experience as an ML Engineer, Data Scientist, or Software Engineer with focus on AI

Qualification:

• BTech in Computer Science, Data Science, Mathematics, or related quantitative field
• MTech in Computer Science, Data Science, Mathematics, or related quantitative field
• PhD in Computer Science, Data Science, Mathematics, or related quantitative field
• or equivalent practical experience

Responsibilities:

• Develop, optimize, and deploy scalable ML/DL models including computer vision, NLP, or LLMs
• Architect robust ML pipelines (MLOps) to automate model training, testing, and deployment
• Collaborate with Data Scientists and Product Managers to integrate AI capabilities into core platform
• Fine-tune models for latency, throughput, and resource utilization in cloud or edge environments
• Stay updated on AI research and evaluate new technologies for product roadmap

Additional responsibilities:

• Work in Agile/Scrum/SAFe processes
• Bridge the gap between data science and software engineering
• Own the lifecycle of machine learning models from conceptualization to production deployment and monitoring
• Demonstrate effectiveness in customer-centric conversations
• Work collaboratively in a cross-cultural environment
• Follow fair and merit-based employee selection and recruitment practices
• Support flexible working arrangements to stimulate innovative thinking

Nice to have:

• Experience with LangChain, LlamaIndex, vector databases, RAGs, and fine-tuning open-source LLMs
• Hands-on experience with cloud platforms AWS, GCP, or Azure
• Ability to design, build, and query Knowledge Graphs
• Familiarity with graph technologies, ontologies, and graph databases
• Strong portfolio of GitHub projects or contributions to open-source AI/ML libraries
• Experience with model deployment using ONNX, TensorRT

More skills:

Computer Vision, OpenCV, YOLO, Hugging Face vision models, MLFlow, DVC, Spark, Kafka, Snowflake, Foundry, RAGs, open-source LLMs, AWS, GCP, Azure, Knowledge Graphs, Neo4j, AWS Neptune, NetworkX, Graph Neural Networks

Other:

• Work at the intersection of code and physical aerospace systems
• Collaborative environment with cutting-edge projects and professional growth opportunities
• Committed to equal opportunity and creating an inclusive and diverse work environment
• No monetary exchange or security deposit required during recruitment
• Awareness of compliance risks and commitment to act with integrity
• Airbus uses and stores applicant information for monitoring purposes
• Encourages applications irrespective of social and cultural background, age, gender, disability, sexual orientation, or religious belief