Data Scientist II leveraging advanced statistical methods and machine learning at F5. Join the Data & Insights team to create impactful data products and drive business success.
About the role
- Data Science/Gen AI Specialist designing applications in NLP/LLM/GenAI for automotive use cases. Collaborating with global teams and working across multiple modalities and data sources.
Responsibilities
- Design NLP/LLM/GenAI applications/products by following robust coding practices.
- Explore SoTA models/techniques so that they can be applied for automotive industry usecases.
- Conduct ML experiments to train/infer models; if need be, build models that abide by memory & latency restrictions.
- Deploy REST APIs or a minimalistic UI for NLP applications using Docker and Kubernetes tools.
- Showcase NLP/LLM/GenAI applications in the best way possible to users through web frameworks (Dash, Plotly, Streamlit, etc.).
- Converge multibots into super apps using LLMs with multimodalities.
- Develop agentic workflow using Autogen, Agentbuilder, langgraph.
- Build modular AI/ML products that could be consumed at scale.
Requirements
- Bachelor’s or master’s degree in computer science, Engineering, Maths or Science
- Performed any modern NLP/LLM courses/open competitions is also welcomed.
- Experience in LLM models like PaLM, GPT4, Mistral (open-source models)
- Work through the complete lifecycle of Gen AI model development, from training and testing to deployment and performance monitoring.
- Developing and maintaining AI pipelines with multimodalities like text, image, audio etc.
- Have implemented in real-world Chat bots or conversational agents at scale handling different data sources.
- Experience in developing Image generation/translation tools using any of the latent diffusion models like stable diffusion, Instruct pix2pix.
- Expertise in handling large scale structured and unstructured data.
- Efficiently handled large-scale generative AI datasets and outputs.
- High familiarity in the use of DL theory/practices in NLP applications.
- Comfort level to code in Huggingface, LangChain, Chainlit, Tensorflow and/or Pytorch, Scikit-learn, Numpy and Pandas.
- Comfort level to use two/more of open source NLP modules like SpaCy, TorchText, fastai.text, farm-haystack, and others.
- Knowledge in fundamental text data processing (like use of regex, token/word analysis, spelling correction/noise reduction in text, segmenting noisy unfamiliar sentences/phrases at right places, deriving insights from clustering, etc.,)
- Have implemented in real-world BERT/or other transformer fine-tuned models (Seq classification, NER or QA) from data preparation, model creation and inference till deployment.
- Familiarity in the use of Docker tools, pipenv/conda/poetry env.
- Comfort level in following Python project management best practices (use of setup.py, logging, pytests, relative module imports,sphinx docs,etc.)
- Familiarity in use of Github (clone, fetch, pull/push,raising issues and PR, etc.)
- Use of GCP services like BigQuery, Cloud function, Cloud run, Cloud Build, VertexAI.
- Good working knowledge on other open-source packages to benchmark and derive summary.
- Experience in using GPU/CPU of cloud and on-prem infrastructures.
- Skillset to leverage cloud platform for Data Engineering, Big Data and ML needs.
- Use of Dockers (experience in experimental docker features, docker-compose, etc.)
- Familiarity with orchestration tools such as airflow, Kubeflow.
- Experience in CI/CD, infrastructure as code tools like terraform etc.
- Kubernetes or any other containerization tool with experience in Helm, Argoworkflow, etc.
- Ability to develop APIs with compliance, ethical, secure and safe AI tools.
- Good UI skills to visualize and build better applications using Gradio, Dash, Streamlit, React, Django, etc.
- Deeper understanding of javascript, css, angular, html, etc., is a plus.
- Skillsets to perform distributed computing (specifically parallelism and scalability in Data Processing, Modeling and Inferencing through Spark, Dask, RapidsAI or RapidscuDF).
- Ability to build python-based APIs (e.g.: use of FastAPIs/ Flask/ Django for APIs).
- Experience in Elastic Search and Apache Solr is a plus, vector databases.
Benefits
- Strong communication skills and do excellent teamwork through Git/slack/email/call with multiple team members across geographies.
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
Associate Data Scientist at Kyndryl's AI Innovation Hub transforming raw data into actionable insights. Collaborating with senior scientists to develop machine learning models and tackle real business challenges.
Data Scientist at PwC creating AI and machine learning solutions. Working with global teams to address diverse business challenges while mentoring junior members.
Data Scientist at Target responsible for developing and managing predictive algorithms using large - scale data. Collaborating with teams to optimize retail solutions and improve decision - making processes.
Consultant(e) Senior - Data IA au sein de Square Management, intervenant sur des enjeux de transformation pour des clients grands comptes.
Senior Manager, Data Science responsible for advanced analytics methodologies at Numeris. Leading a team to ensure accuracy and reliability of data products and processes.
Data Scientist providing data - driven insights to inform business strategy at Mixpanel. Collaborating with leadership to shape research initiatives and drive positive organizational change.
Senior AI/ML Platform Architect for Instructure building AWS - native infrastructure for AI/ML services, translating needs into scalable architecture.
Lead Analyst driving AI - enabled data capabilities across RCM organization in Hyderabad. Collaborating with interdisciplinary teams for machine learning model development and actionable insights.
Data Science Intern at Ekimetrics supporting marketing effectiveness and strategy with data analysis and modeling techniques. Engage with cross - functional teams and contribute to client deliverables.