Senior Member of Technical Staff, AI Research
Relha LLC, Palo Alto, CA, United States
Senior Member of Technical Staff, AI Research
Overview
Salesforce AI Research is looking for a Machine Learning Engineer to incubate next‑generation agentic AI platforms. You will work closely with research scientists, software engineers, product managers and solution engineers to design, implement, and iterate agentic AI systems with customers.
With strong technical competence, strategic thinking, and customer engagement, you will innovate at the frontier of the field, creating new solutions and defining new product categories with meaningful impact on Salesforce customers and beyond.
Responsibilities
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Build and ship high‑quality, production‑grade software using modern engineering practices, with AI as a core part of the development workflow.
Contribute to the shared system context, maintaining a repository of system designs, constraints, and standards for reliable AI operation.
Critically evaluate code—human or AI generated—for correctness, quality, security, and performance.
Implement and debug model training, evaluation, and inference pipelines.
Deploy ML systems using Docker and cloud platforms (AWS, GCP, or Azure).
Familiarity with distributed training, inference, and performance optimization.
Apply advanced prompt engineering skills to write precise, structured prompts and cultivate system context that makes AI outputs reliable, secure, and production‑ready.
Qualifications
Exceptional engineering skills and strong software engineering fundamentals (data structures, algorithms, system design).
Deep machine‑learning knowledge with meaningful implementation track record.
Strategic thinker who prioritizes deep and strategic problem‑solving.
Proactive, resilient, and collaborative, thriving in a fast‑paced environment.
Dedicated, patient, and committed to building an exceptional product experience.
Technical Skills
Strong proficiency in Python; solid experience with C++ and/or Java.
Hands‑on experience with deep learning frameworks and LLMs.
Experience building production‑quality systems, including agentic/LLM systems, end‑to‑end AI agents, and complex AI‑driven applications.
Familiarity with prompting, orchestration, and evaluation for LLM‑based systems.
Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure).
Experience
Practical experience with LLMs and agentic workflows (tool use, planning, memory, multi‑step reasoning).
Experience deploying, scaling, and optimizing ML systems.
Competitive coding experience (e.g., ACM‑ICPC) is desirable.
For doctoral candidates: 2–3 first‑author high‑impact papers (≥500 citations) or one first‑author stellar paper (≥3,000 citations).
For undergrads/masters: at least one high‑impact paper (≥500 citations) or relevant open‑source contributions with ≥2,000 stars.
Benefits
Competitive base salary range and potential incentive compensation, equity, and benefits.
Paid time off, medical, dental, vision, mental health support, and paid parental leave.
Life and disability insurance, 401(k) and an employee stock purchasing program.
Commitment to equitable compensation practices reflecting labor market dynamics.
Posting Statement
Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. The company assesses employees and applicants on the basis of merit, competence, and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law.
Accommodations
Requests for reasonable accommodations during the application or recruiting process can be submitted via the Accommodations Request Form.
#J-18808-Ljbffr
Overview
Salesforce AI Research is looking for a Machine Learning Engineer to incubate next‑generation agentic AI platforms. You will work closely with research scientists, software engineers, product managers and solution engineers to design, implement, and iterate agentic AI systems with customers.
With strong technical competence, strategic thinking, and customer engagement, you will innovate at the frontier of the field, creating new solutions and defining new product categories with meaningful impact on Salesforce customers and beyond.
Responsibilities
Design and orchestrate complex systems where AI agents integrate seamlessly into human workflows, driving efficiency and innovation at scale.
Build and ship high‑quality, production‑grade software using modern engineering practices, with AI as a core part of the development workflow.
Contribute to the shared system context, maintaining a repository of system designs, constraints, and standards for reliable AI operation.
Critically evaluate code—human or AI generated—for correctness, quality, security, and performance.
Implement and debug model training, evaluation, and inference pipelines.
Deploy ML systems using Docker and cloud platforms (AWS, GCP, or Azure).
Familiarity with distributed training, inference, and performance optimization.
Apply advanced prompt engineering skills to write precise, structured prompts and cultivate system context that makes AI outputs reliable, secure, and production‑ready.
Qualifications
Exceptional engineering skills and strong software engineering fundamentals (data structures, algorithms, system design).
Deep machine‑learning knowledge with meaningful implementation track record.
Strategic thinker who prioritizes deep and strategic problem‑solving.
Proactive, resilient, and collaborative, thriving in a fast‑paced environment.
Dedicated, patient, and committed to building an exceptional product experience.
Technical Skills
Strong proficiency in Python; solid experience with C++ and/or Java.
Hands‑on experience with deep learning frameworks and LLMs.
Experience building production‑quality systems, including agentic/LLM systems, end‑to‑end AI agents, and complex AI‑driven applications.
Familiarity with prompting, orchestration, and evaluation for LLM‑based systems.
Experience with Docker, Kubernetes, and cloud platforms (AWS, GCP, Azure).
Experience
Practical experience with LLMs and agentic workflows (tool use, planning, memory, multi‑step reasoning).
Experience deploying, scaling, and optimizing ML systems.
Competitive coding experience (e.g., ACM‑ICPC) is desirable.
For doctoral candidates: 2–3 first‑author high‑impact papers (≥500 citations) or one first‑author stellar paper (≥3,000 citations).
For undergrads/masters: at least one high‑impact paper (≥500 citations) or relevant open‑source contributions with ≥2,000 stars.
Benefits
Competitive base salary range and potential incentive compensation, equity, and benefits.
Paid time off, medical, dental, vision, mental health support, and paid parental leave.
Life and disability insurance, 401(k) and an employee stock purchasing program.
Commitment to equitable compensation practices reflecting labor market dynamics.
Posting Statement
Salesforce is an equal‑opportunity employer and maintains a policy of non‑discrimination with all employees and applicants for employment. The company assesses employees and applicants on the basis of merit, competence, and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law.
Accommodations
Requests for reasonable accommodations during the application or recruiting process can be submitted via the Accommodations Request Form.
#J-18808-Ljbffr