Reveal Health Tech
Staff Software Engineer- Lead
Reveal Health Tech, San Francisco, California, United States, 94199
Job Title:
Staff Software Engineer- Lead
Location:
Hybrid at San Francisco, CA
Start Date:
Immediate
Visa Sponsorship:
Not at the moment
Requirements
As the Lead of a software engineering team, you will oversee the full software and model development lifecycle, working with various business and technology stakeholders.
Team Responsibilities:Develop Architectures:
Design and implement scalable architectures for deploying and maintaining ML and AI solutions.Build Infrastructure:
Create and manage infrastructure components and CI/CD pipelines and extend existing ML services on AWS.Evaluate Techniques:
Assess retrieval methods, language models, and generative AI techniques with a focus on practical solutions.Ensure Quality:
Implement automated testing and monitoring to maintain AI system accuracy and reliability.Collaborate Cross-Functionally:
Collaborate with data scientists, software engineers, and other cross-functional teams including our engineering team in India, facilitate data-driven decision making, and drive innovative solutions.Optimize Solutions:
Partner with the MLOps team to enhance AI/ML solutions for performance and scalability.Mentor Team:
Guide and coach team members on engineering best practices.Drive Innovation:
Stay current with AI advancements to foster innovation.Documentation:
Document and communicate methodologies, algorithms, findings, and recommendations to technical and non-technical stakeholders.Desired Qualifications:
Please note that while you do not need to be an expert in every area, being familiar with most of the following is important. We are looking for someone who can effectively integrate everything, with team support to fill any gaps.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.Proficiency in Python and experience with machine learning models at scale.Extensive knowledge of AI/ML technologies, including libraries like scikit-learn, PyTorch, and Transformers.Hands-on experience with Docker, AWS (ECS, Lambdas, API Gateway), and ML/Gen AI services (AWS Bedrock, SageMaker).Familiarity with CI/CD pipelines (Jenkins, GitHub Actions) and version control.Strong understanding of retrieval-augmented generation (RAG), chains, routing, and vector databases.Knowledge of MLOps practices, model development, deployment, and performance monitoring, including LLM use cases.Ideally, hands-on experience with model training, fine-tuning, evaluation, and risk mitigation in production environments.Proven ability to lead and scale projects from prototype to production with hands on experience working on user-facing products.Experience with life sciences or healthcare data is a plus.Benefits
How will you enrich Us
Energetic and EnthusiasticAutonomous and self-motivatedGrowth mindsetEmbraces challengesChallenges the status quo constructively
If you meet the qualifications and are excited about this opportunity, please submit your resume. We are looking to fill this role immediately and will review applications on a rolling basis.
Staff Software Engineer- Lead
Location:
Hybrid at San Francisco, CA
Start Date:
Immediate
Visa Sponsorship:
Not at the moment
Requirements
As the Lead of a software engineering team, you will oversee the full software and model development lifecycle, working with various business and technology stakeholders.
Team Responsibilities:Develop Architectures:
Design and implement scalable architectures for deploying and maintaining ML and AI solutions.Build Infrastructure:
Create and manage infrastructure components and CI/CD pipelines and extend existing ML services on AWS.Evaluate Techniques:
Assess retrieval methods, language models, and generative AI techniques with a focus on practical solutions.Ensure Quality:
Implement automated testing and monitoring to maintain AI system accuracy and reliability.Collaborate Cross-Functionally:
Collaborate with data scientists, software engineers, and other cross-functional teams including our engineering team in India, facilitate data-driven decision making, and drive innovative solutions.Optimize Solutions:
Partner with the MLOps team to enhance AI/ML solutions for performance and scalability.Mentor Team:
Guide and coach team members on engineering best practices.Drive Innovation:
Stay current with AI advancements to foster innovation.Documentation:
Document and communicate methodologies, algorithms, findings, and recommendations to technical and non-technical stakeholders.Desired Qualifications:
Please note that while you do not need to be an expert in every area, being familiar with most of the following is important. We are looking for someone who can effectively integrate everything, with team support to fill any gaps.
Bachelor's or Master's degree in Computer Science, AI, Data Science, or a related field.Proficiency in Python and experience with machine learning models at scale.Extensive knowledge of AI/ML technologies, including libraries like scikit-learn, PyTorch, and Transformers.Hands-on experience with Docker, AWS (ECS, Lambdas, API Gateway), and ML/Gen AI services (AWS Bedrock, SageMaker).Familiarity with CI/CD pipelines (Jenkins, GitHub Actions) and version control.Strong understanding of retrieval-augmented generation (RAG), chains, routing, and vector databases.Knowledge of MLOps practices, model development, deployment, and performance monitoring, including LLM use cases.Ideally, hands-on experience with model training, fine-tuning, evaluation, and risk mitigation in production environments.Proven ability to lead and scale projects from prototype to production with hands on experience working on user-facing products.Experience with life sciences or healthcare data is a plus.Benefits
How will you enrich Us
Energetic and EnthusiasticAutonomous and self-motivatedGrowth mindsetEmbraces challengesChallenges the status quo constructively
If you meet the qualifications and are excited about this opportunity, please submit your resume. We are looking to fill this role immediately and will review applications on a rolling basis.