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Senior Data Scientist

North America Req #30
Tuesday, November 7, 2023

At Converge Technology Solutions, we're at the forefront of cutting-edge technology and innovation. We are seeking a highly skilled and experienced Generative AI Data Scientist & Technical Consultant to join our team and play a pivotal role in helping our customers harness the power of Generative AI services. In this multifaceted role, you will serve as both a subject matter expert and a technical consultant, taking a lead in pre-sales calls, as well as delivering innovative solutions to our valued clients.

Key Responsibilities:

1. Customer Advisor:

   - Collaborate with our clients to design and implement state-of-the-art Generative AI solutions.

   - Develop prototypes, proof of concepts, and explore novel solutions tailored to their specific needs.

   - Work closely with customers and engage with the academic community to push the boundaries of AI.

2. Thought Leadership:

   - Champion our Generative AI services, sharing best practices and expertise through publications, industry events, and public speaking engagements.

3. Collaboration and Support:

   - Partner with Solutions Architects, Sales, Business Development, and AI/ML Delivery teams to accelerate customer adoption.

   - Act as a technical liaison between customers and our internal service teams, providing valuable customer-driven feedback for product improvement.

4. Community Building:

   - Foster a community of machine learning experts within our organization and help them understand how to integrate Generative AI solutions into customer architectures.

   - Create field enablement materials to educate our broader Solutions Architect population on integrating Generative AI solutions into customer architectures.

Desired Skills and Qualifications:


- 3+ years of experience as a data scientist, specializing in machine learning and AI.

- Proficiency in Python, including experience with machine learning libraries such as scikit-learn, PyTorch, TensorFlow, and NLP frameworks with a minimum of 3 years of practical experience.

- Experience using LangChain, LlamaIndex, RAG, vector databases, and prompt engineering

- 3+ years of Data querying languages such as SQL, GraphQL or similar

- Master's degree in a quantitative field such as statistics, mathematics, data science, business analytics, economics, finance, engineering, or computer science.

- A minimum of 2 years of hands-on experience in researching and applying large language and generative AI models.

- Strong expertise in Natural Language Processing, including text representation, language modeling, sequence-to-sequence architectures, and semantic understanding.

- 3+ years of practical experience in technical architecture, design, deployment, and operational knowledge in the field of machine learning.

 Preferred Additional Experience:

- Expertise in LangChain, LlamaIndex, RAG, FM tuning, Data Augmentation, and model performance observability.

- Involvement in the open-source LLM community, such as HuggingFace and StableDiffusion

- Experience with large models pretraining/fine-tuning and familiarity with distributed training.

- Exceptional customer-facing skills, capable of engaging with senior level stakeholders across different organizations.

- Proven capacity to approach business, product, and technical complexities strategically within an enterprise setting, backed by a history of pioneering thought leadership and innovation in the field of Machine Learning.

 Technical Skills:

- Programming: Proficiency in Python as the primary programming language.

- Machine Learning Libraries: Expertise in using cutting-edge tools and libraries including scikit-learn, PyTorch, JAX, and TensorFlow to develop and deploy machine learning models.

- Natural Language Processing (NLP): Profound knowledge and practical experience with NLP tools such as spaCy, NLTK, or HuggingFace Transformers for advanced language processing.

- Generative AI: Familiarity with state-of-the-art generative AI models like GPT-3, GPT-4, or OpenAI's DALL-E for image and text generation.


- Cloud experience/DevOps: Proficiency in DevOps tools such as Docker, Kubernetes, and GitHub actions or similar for managing and deploying machine learning models in a containerized environment. Experience in leveraging AWS (Sagemaker), IBM Cloud (WatsonX), Azure (ML/ML Studio) or GCP (Vertex AI) for building out tailored solutions using their cloud services.

- MLOps: Expertise in MLOps tools like MLflow, Kubeflow, or similar to streamline the machine learning lifecycle, including model versioning and automated deployment.



Converge Technology Solutions provides equal employment opportunities to all employees and applicants for employment and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws. This policy applies to all terms and conditions of employment, including recruiting, hiring, placement, promotion, termination, layoff, recall, transfer, leaves of absence, compensation and training.

Other details

  • Job Family Information Technology
  • Pay Type Salary
  • Required Education Bachelor’s Degree
Location on Google Maps
  • North America