Data Scientist / LLM Engineer

As a Data Scientist specializing in LLM you will be responsible for developing, implementing and optimizing advanced algorithms, models and capabilities that help our teams (e.g. Field Operations) automate their workloads, e.g. in the context of decision support, mission planning and situational awareness. You will work on a variety of projects that involve understanding, processing and generating human language to solve complex problems and create innovative solutions. The ideal candidate will have a strong background in LLMs, machine learning and data science, with a proven track record of successful projects in these domains.

 

What will be your responsibilities:

• Algorithm Development: Design, develop and implement state-of-the-art algorithms and models, within the context of language models.
• Capability Development: Realize new AI-based capabilities in areas such as decision support, mission planning, workflow automation.
• Model Training and Optimization: Train and optimize large language models using vast amounts of textual data, ensuring high performance and accuracy.
• Data Preprocessing: Perform data preprocessing tasks such as tokenization, stemming, lemmatization and normalization to prepare datasets for training and evaluation.
• Research and Innovation: Stay current with the latest advancements in LLM and Natural Language Processing (NLP) and apply new techniques to improve existing models and develop new solutions.
• Collaboration: Work closely with data engineers, software developers, product managers and other stakeholders to understand project requirements and deliver effective solutions.
• Performance Evaluation: Evaluate the performance of models using appropriate metrics and techniques and iteratively improve their accuracy and efficiency.
• Deployment: Collaborate with engineering teams to deploy models into production environments and ensure their robustness and scalability.
• Documentation: Maintain comprehensive documentation of models, algorithms and processes for future reference and reproducibility.

 

Profile and requirements:

• Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. A Ph.D. is a plus.
• Experience: 3+ years of experience in data science, with a focus on large language models and NLP.
• Technical Skills:
  • Strong programming skills in Python and experience with NLP libraries and models such as NLTK, spaCy, Hugging Face Transformers and GPT-3/GPT-4, LLaMA.
  • Proficiency in machine learning frameworks such as TensorFlow, TensorRT, PyTorch, Keras.
  • Experience with data preprocessing techniques.
  • Knowledge of deep learning architectures and techniques for NLP, including transformers, RNNs and CNNs.
  • Experience with training and fine tuning Large Language Models and building RAG agents.
  • Experience with experimentation platforms such as Jupyter Notebooks.
  • Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and their AI services, with a focus on Google Cloud.
  • Experience in deploying self-hosted LLMs.
  • Basic Knowledge of DevOps best practices and tools: GIT, CI/CD, telemetry and monitoring, etc.
• Analytical Skills: Excellent analytical and problem-solving skills with the ability to design innovative solutions to complex problems.
• AI Ethics and Bias Mitigation: Experience or awareness of AI ethics, fairness and bias mitigation strategies, in the context of NLP and LLMs.
• Communication: Strong verbal and written communication skills, with the ability to explain complex technical concepts to non-technical stakeholders.
• Collaboration: Ability to work effectively in a collaborative, cross-functional team environment.
• Attention to Detail: High attention to detail and a commitment to ensuring the accuracy and quality of work.
• Adaptability: Ability to thrive in a fast-paced, dynamic environment and manage multiple projects simultaneously.