Experienced Full Stack Data Scientist – Multimodal Foundation Model Evaluation and Development
Are you passionate about pushing the boundaries of artificial intelligence and machine learning? Do you have a knack for analyzing complex data and developing innovative solutions? If so, we invite you to join arenaflex, a leading innovator in the tech industry, as a Full Stack Data Scientist. In this role, you will play a critical part in the evaluation and development of multimodal foundation models, working closely with a talented team of engineers, data scientists, and researchers.
About arenaflex
arenaflex is a cutting-edge technology company that is revolutionizing the way we interact with technology. With a focus on innovation and excellence, we are constantly pushing the boundaries of what is possible. Our team is comprised of talented individuals from diverse backgrounds, united by a shared passion for learning and growth. We believe in creating a work environment that is inclusive, supportive, and stimulating, where our employees can thrive and reach their full potential.
Job Summary
We are seeking a highly skilled and motivated Full Stack Data Scientist to join our Data Logical and Quality (DAQ) team. As a key member of this team, you will be responsible for evaluating and developing multimodal foundation models, working closely with our engineers, data scientists, and researchers. Your primary responsibilities will include:
- Developing methods for the evaluation and improvement of foundation models
- Refining the data used in setting up these models, utilizing data-driven machine learning techniques
- Collaborating with our team to design and implement experiments and client studies
- Working with various stakeholders to identify and address data quality issues
- Contributing to the development of new features and expected client experiences based on data insights
Key Responsibilities
* Conduct in-depth analysis of multimodal foundation models to identify areas for improvement
- Develop novel evaluation and benchmark strategies from foundation model composing research
- Create tools for data separation and visualization
- Design and implement experiments and client studies to test and validate new models
- Collaborate with our data engineering and research teams to identify and address data quality issues
- Contribute to the development of new features and expected client experiences based on data insights
Essential Qualifications
* Bachelor's degree in Computer Science, Data Science, or a related field
- At least 3 years of experience in data science, machine learning, and/or computer vision
- Strong foundation in data science, machine learning, computer vision, and artificial intelligence
- Proven experience in thorough assessment of AI model frustrations
- Demonstrated expertise in data and model appraisal
- Ability in data-driven machine learning
- Familiarity with various foundation models, such as SAM, LLAMA, LLaVA, CGPT4V, and Catch
- Proficiency in at least one programming language, preferably Python
- Experience with logical tools like Jupyter, Pandas, NumPy, and Matplotlib
- Strong verbal and written communication skills, along with excellent collaboration and teamwork abilities
Preferred Qualifications
* Experience in preparing models using frameworks like PyTorch, TensorFlow, Jax, etc.
- Familiarity with data visualization tools like Matplotlib, Seaborn, and Plotly
- Experience with cloud-based platforms like AWS, GCP, or Azure
- Knowledge of agile development methodologies and version control systems like Git
What We Offer
* Competitive salary and benefits package
- Opportunity to work with a talented team of engineers, data scientists, and researchers
- Collaborative and inclusive work environment
- Professional development and growth opportunities
- Flexible work arrangements, including remote work options
- Access to cutting-edge technology and tools
- Recognition and rewards for outstanding performance
How to Apply
If you are a motivated and talented individual who is passionate about data science and machine learning, we encourage you to apply for this exciting opportunity. Please submit your resume, cover letter, and any relevant work samples or projects you would like to share. We look forward to hearing from you! Apply To This Job Apply for this job