Data Solutions Architect

Sphere Software; United States; Remote; USD 120,000 - 180,000; Full time

Job summary

Sphere Software is seeking an AI Architect to leverage expertise in generative AI solutions and Large Language Models. The role involves developing and optimizing AI applications, collaborating with teams, and innovating on technology within a flexible remote work environment. Candidates should possess strong programming skills and cloud platform experience, particularly with AWS.

Benefits

Competitive salary and benefits

Flexible work environment

International travel opportunities

Qualifications

• At least 3 years of experience in creating AI solutions using Databricks.
• Minimum of 5 years of programming experience in Python and SQL.
• Proficiency in diverse data storage systems, including RDMS and NoSQL.

Responsibilities

• Develop generative AI solutions utilizing AWS services.
• Contribute to the development and application of Large Language Models.
• Optimize and fine-tune generative models for performance and efficiency.

Skills

Data preprocessing

Feature engineering

Database management

Python

SQL

Machine Learning

Deep Learning

Cloud computing

Education

Bachelor's or Master's in Computer Science or related field

Tools

AWS

Databricks

TensorFlow

PyTorch

Keras

Job description

Sphere combine global expertise and local insight to help people and companies to turn their ambitious goals into reality. At Sphere we put people first and strive to be a changemaker by building a better future through innovation and technology. Now we are looking for an AI Architect to join our team and help our customers to improve their service.

Location:Remotely
Type:Contract
Start Date:ASAP

Responsibilities:

• Develop Generative AI solutions utilizing AWS services, including S3, Redshift, and Snowflake, across various client teams;
• Contribute to the development and application of Large Language Models (LLMs) and Generative AI;
• Explore new areas within LLMs and Generative AI, translating research into practical applications;
• Communicate complex technical concepts and findings to non-technical stakeholders;
• Collaborate with cross-functional teams to integrate generative AI solutions into existing workflow systems;
• Stay updated on the latest advancements in generative AI technologies and methodologies;
• Optimize and fine-tune generative models for performance and efficiency;
• Troubleshoot and resolve issues related to generative AI models and implementations;
• Create and maintain documentation for generative AI models and their applications;
• Deploy and monitor Machine Learning models, focusing on generative AI and LLM-based agents;
• Design and develop prototypes in collaboration with IT practitioners and client stakeholders;
• Evaluate new tools and technologies, selecting appropriate ones for efficient and quality deliverables;
• Demonstrate confidence and ability to work in ambiguous situations;
• Influence business decisions by providing recommendations and trade-offs;
• Engage in continuous research and learning to attain in-depth knowledge of capabilities, limitations, internal architecture, and applications of a broad range of trending tech stacks, presenting essential comparisons, pros/cons, and target use cases;
• Assist leadership in building or upgrading reference architectures, developing new service lines or enhancing existing ones, and designing and implementing programs to align delivery teams with new or enhanced service offerings;
• Lead training programs to help the next generation gain technical expertise.

Requirements:

• At least 3 years of experience in creating AI solutions using Databricks (certification is a plus);
• Experience with generative AI frameworks, such as LlamaIndex and Langchain;
• Familiarity with generative AI models from OpenAI, Google, or open-source alternatives (e.g., Llama, Claude, Hugging Face);
• Minimum of 5 years of programming experience in Python and SQL;
• Proficiency in diverse data storage systems, including RDMS and NoSQL;
• Expertise in utilizing major cloud platforms, with a strong emphasis on AWS (minimum 2-3 years of experience) and knowledge of Azure;
• Understanding of neural network architectures, such as Generative Adversarial Networks (GANs) and Transformers;
• Experience using TensorFlow, PyTorch, and Keras for designing, training, and validating AI models;
• Familiarity with CI/CD solutions in the context of MLOps and LLMOps, including automation with Infrastructure as Code (IaC) tools like Biceps or Terraform;
• Skills in data preprocessing and feature engineering for AI model training;
• Knowledge of designing and explaining data pipelines, ML pipelines, and ML training and serving methodologies;
• Experience in deploying ML models using native infrastructure (e.g., Azure DevOps, Databricks) or third-party MLOps platforms;
• Understanding of specific domains or industries and the application of NLP/LLM solutions;
• Demonstrated innovative mindset and problem-solving abilities;
• Awareness of AI standards and the ability to assess and mitigate technology risks;
• Excellent communication and presentation skills.

Sphere offers a competitive and rewarding salary and benefits package, as well as an intellectually and creatively stimulating work environment, flexibility, and unique international travel opportunities.