AI-Engineer (GenAI)

We are seeking a talented and motivated Junior GenAI Engineer with 3-5 years of professional experience to join our innovative and growing this role you will play a crucial part in designing developing and deploying advanced Generative AI models with a particular focus on Text Analytics Natural Language Processing (NLP) and Deep Learning techniques. You will work on challenging problems that directly impact our products and services contributing to the next generation of intelligent systems.

Roles & Responsibilities:

• Model Development & Implementation: Design develop and implement Generative AI models (e.g. LLMs GANs VAEs for text) for various applications leveraging your expertise in Text Analytics NLP and Deep Learning.

• Data Preprocessing & Feature Engineering: Clean preprocess and analyze large textual datasets to prepare them for model training. Design and implement effective feature engineering strategies for NLP tasks.

• Experimentation & Optimization: Conduct rigorous experimentation to evaluate model performance identify areas for improvement and optimize model architectures and hyperparameters.

• Research & Innovation: Stay abreast of the latest research and advancements in Generative AI NLP and Deep Learning. Propose and explore novel approaches to solve complex problems.

• Deployment & MLOps (early exposure): Assist in the deployment of AI models into production environments contributing to monitoring maintenance and performance tuning. (Opportunity to learn and grow into MLOps practices).

• Collaboration & Communication: Work closely with senior engineers data scientists product managers and other stakeholders to understand requirements share insights and deliver impactful solutions.

• Documentation: Document code models and processes thoroughly to ensure maintainability and knowledge sharing.

Qualifications :

Educational qualification:

Bachelors or Masters degree in Computer Science Artificial Intelligence Machine Learning Data Science or a related quantitative field.

Experience :

• Experience: 3-5 years of professional experience in roles focused on Machine Learning Deep Learning Natural Language Processing or Text Analytics.

Mandatory/requires Skills :

 Strong Foundation in NLP & Text Analytics:

• Solid understanding of core NLP concepts (e.g. tokenization stemming lemmatization parsing named entity recognition sentiment analysis).

• Experience with various NLP techniques and libraries (e.g. NLTK SpaCy Transformers).

• Proven ability to work with large unstructured text datasets.

 Deep Learning Expertise:

• Hands-on experience with deep learning frameworks such as TensorFlow PyTorch or JAX.

• Proficiency in designing and implementing various neural network architectures (e.g. CNNs RNNs LSTMs Transformers).

• Understanding of key deep learning concepts like backpropagation optimization algorithms and regularization.

 Generative AI Interest/Exposure:

• Strong interest in and foundational understanding of Generative AI concepts (e.g. LLMs diffusion models GANs VAEs attention mechanisms specialized models to support multi-modality).

• Experience working with pre-trained language models (e.g. BERT GPT T5) for fine-tuning and adaptation.

• Experience with model fine-tuning techniques like LoRA Q-LoRA tools like LlamaFactory for model fine-tuning

• Exposure to Agentic AI-based design patterns prompt engineering and platforms to build multi-agentic systems e.g. LangGraph Smolagents CrewAI Autogen n8n

• Evaluation techniques for Agentic systems like using LangSmith

• Strong interest in building tools using popular standards like MCP A2A ACP etc.

 Programming Proficiency: Expert-level proficiency in Python including relevant libraries for data science and machine learning (NumPy Pandas Scikit-learn).

 Problem-Solving Skills: Excellent analytical and problem-solving abilities with a keen eye for detail and a data-driven approach.

 Communication Skills: Strong verbal and written communication skills with the ability to explain complex technical concepts clearly to both technical and non-technical audiences.

 Team Player: Ability to work effectively in a collaborative team environment and contribute to a positive and innovative culture.

Preferred Skills :

• Experience with cloud platforms (AWS Azure GCP) for deploying and managing AI/ML workloads.

• Familiarity with LLMOps MLOps principles and tools (e.g. MLflow Kubeflow Docker Kubernetes).

• Experience with distributed computing frameworks (e.g. Spark Dask).

• Contributions to open-source projects in NLP or Generative AI.

• Published research papers or participation in Kaggle competitions related to NLP/Deep Learning.

• Experience with prompt engineering and fine-tuning large language models for specific tasks.

Additional Information :

Why Bosch Research

At Bosch Research you will work on solving real-world industrial problems with the full support of Boschs global innovation network. This role combines deep technical execution with strategic leadership offering the unique opportunity to shape the future of AI/ML at Bosch and beyond.

Remote Work :

No

Employment Type :

Full-time