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Requirements:
Required Qualifications
Bachelors or Practical Engineering degree in Mechanical or Electrical disciplines, or related field Minimum of 5 years of experience in NPI and/or Production engineering, preferably in UAV, aerospace, or defence industries Hands-on experience with UAV systems, drones, or aerospace assemblies Strong understanding of: Mechanical assemblies (composites, structures, precision parts) Electrical systems (wiring, harnessing, PCB integration) system integration and testing Experience with PLM/ ERP systems (e.g., Teamcenter, Priority, SAPgreenTxtBg!) Proficiency in CAD tools (e.g., SolidWorks) Proficiency in English (verbal and written)

Preferred Qualifications and Experience
Experience in UAV platforms, preference to VTOL and/or Fixed-Wing systems Familiarity with flight testing, ground control systems, and payload integration Knowledge of aerospace standards (e.g. ISO9001, AS9100) Experience in military or commercial UAV programs Experience with composite materials and lightweight structures Background in electronics manufacturing or Embedded systems Experience working in high-mix, low-volume production environments

Requirements:
Minimum of 3 years of experience with the Python programming language and Pythons scientific libraries, such as NumPy, SciPy, and Scikit-Learn
Good understanding of Machine Learning models: optimization, clustering, NLP, time series, etc.
Excellent knowledge of database management systems (SQL/NoSQL) and experience with data structures.
Ability to work collaboratively and communicate effectively with professionals across a range of technical and non-technical backgrounds
Experience in designing and developing APIs.
Hands-on experience with cloud-based solutions for application architecture and deployment.
Experience with Git
Bachelors degree in computer science, information technology, mathematics, or an equivalent field
Nice to have: Experience in building web applications

Requirements:
Requirements 5+ years of hands-on Python development experience, with expertise in building and deploying AI and Machine Learning applications - mandatory. Extensive hands-on experience with AWS services relevant to AI/ML, including S3, Glue, Athena, SageMaker, Lambda, and Bedrock - mandatory. Proven experience with Generative AI frameworks such as LangChain, LlamaIndex, or Haystack - mandatory. Hands-on experience designing and deploying RAG-based applications, along with practical knowledge of Vector Databases such as Pinecone, Weaviate, or ChromaDB and document indexing techniques - mandatory. Strong understanding of software development principles, including Git version control, clean code practices, and Unit Testing - mandatory. Strong analytical and problem-solving skills, with the ability to break down complex business challenges into actionable technical solutions - mandatory. Excellent communication and collaboration skills, with the ability to clearly explain technical concepts to both technical and non-technical stakeholders - mandatory. Nice to Have: Domain Knowledge: Previous experience in the financial services, fintech, or a related highly-regulated industry. Database Experience: Experience with specialized databases such as graph databases (e.g., Neo4j, Amazon Neptune). MLOps Tools: Familiarity with MLOps platforms beyond AWS, such as Kubeflow or MLflow. Education: A Master's or Ph.D. in Computer Science, AI, or a related field.