職種概要
You’ll apply generative AI across the software development lifecycle for embedded products, from requirements analysis and coding to code review, testing, and documentation. You’ll learn how target hardware constraints and project requirements for quality, traceability, and code confidentiality shape embedded development, and adapt AI tools and workflows accordingly.
You will work alongside experienced engineers who bring deep domain knowledge, with a strong focus on practical skills, hands-on experimentation, and mentoring-driven growth. Curiosity, structured thinking, and the ability to critically evaluate AI output are key to this position. We also expect a responsible, communicative team player who is ready to learn, ask questions, and share findings.
必要条件
We are looking for a Trainee AI Engineer (Generative AI) to join our AI-DLC initiatives in the embedded domain. This role suits a candidate who is already confident with GenAI and LLM tooling and wants to apply it to embedded software development, working side by side with experienced embedded engineers to build AI-assisted workflows tailored to the specifics of these projects.
You will help rapidly prototype ideas, build small PoCs, and experiment with solutions based on large language models (LLMs) and other generative AI techniques. Your focus will be to implement well-defined tasks, run experiments, and use GenAI tools to speed up coding, analysis, and documentation – while learning how to do this safely and reliably in production-oriented environments.
Required Qualifications:
- Practical experience in software development, data science, or ML (commercial experience, internships, or strong personal projects).
- Solid basic skills in Python and core data/ML libraries (e.g., NumPy, pandas, Scikit-learn).
- Understanding of fundamental ML concepts (datasets, train/validation split, basic metrics, overfitting).
- Practical familiarity with generative AI / LLMs:
– regular use of tools like ChatGPT, Copilot or similar for coding and data tasks;
– basic understanding of prompts, context windows, and common limitations (hallucinations, privacy, bias). - High motivation to learn, ask questions, and accept feedback.
- Organized and responsible: able to follow a spec, document work, and meet agreed timelines.
Preferred Qualifications:
- Bachelor’s or Master’s degree in Computer Science, Data Science, AI, or a related field.
- Coursework, pet projects, or a thesis related to ML, NLP, or Generative AI.
- Basic exposure to RAG, embeddings, or vector databases (from articles, courses, or small experiments).
- Familiarity with at least one cloud platform (Azure, AWS, or GCP) from labs or online coursesю.
- Experience with Jupyter notebooks, Git, and simple CI/CD or MLOps tools (even at a “student project” level).
- Participation in hackathons, Kaggle competitions, or open-source projects.
職務内容
- Rapidly prototype and iterate on ML / GenAI ideas in notebooks and scripts, turning high-level concepts into small PoCs and demo flows.
- Implement well-defined tasks in Python (data preprocessing, basic model training, evaluation scripts, and utility functions) as part of prototypes and production-oriented components.
- Assist in experiments with LLMs and GenAI APIs (prompt variants, small workflows, simple RAG setups) under the guidance of senior engineers, proactively suggesting new options and documenting what works and what doesn’t.
- Use GenAI tools to support your daily work (coding, tests, documentation, exploratory analysis) and capture key findings in a clear, structured way.
- Prepare and clean datasets, run experiments, and summarize results in concise formats (tables, short reports, simple dashboards).
- Help build and maintain demo environments and internal PoCs for ML / GenAI use cases, keeping them reproducible and easy to reuse.
- Follow coding standards, version control practices, and basic quality processes (code reviews, simple tests, logging).
- Actively learn from senior team members, ask questions, and gradually take ownership of small components within larger solutions.
私たちが提供するもの
Empowering Projects: With 500+ clients spanning diverse industries and domains, we provide an exciting opportunity to contribute to groundbreaking projects that leverage cutting-edge technologies. As a team, we engineer digital products that positively impact people’s lives.
Empowering Growth: We foster a culture of continuous learning and professional development. Our dedication is to provide timely and comprehensive assistance for every consultant through our dedicated Learning & Development team, ensuring their continuous growth and success.
DE&I Matters: At GlobalLogic, we deeply value and embrace diversity. We are dedicated to providing equal opportunities for all individuals, fostering an inclusive and empowering work environment.
Career Development: Our corporate culture places a strong emphasis on career development, offering abundant opportunities for growth. Regular interactions with our teams ensure their engagement, motivation, and recognition. We empower our team members to pursue their career goals with confidence and enthusiasm.
Comprehensive Benefits: In addition to equitable compensation, we provide a comprehensive benefits package that prioritizes the overall well-being of our consultants. We genuinely care about their health and strive to create a positive work environment.
Flexible Opportunities: At GlobalLogic, we prioritize work-life balance by offering flexible opportunities tailored to your lifestyle. Explore relocation and rotation options for diverse cultural and professional experiences in different countries with our company.
GlobalLogicについて
GlobalLogic, a Hitachi Group Company, is a trusted digital engineering partner to the world’s largest and most forward-thinking companies. Since 2000, we’ve been at the forefront of the digital revolution – helping create some of the most innovative and widely used digital products and experiences. Today we continue to collaborate with clients in transforming businesses and redefining industries through intelligent products, platforms, and services.
