AI Specialist - Cloud & AI Solutions
Job ID
6671
Location
SLAC - Menlo Park, CA
Full-Time
Regular
SLAC Job Postings
Position Overview:
Join the dynamic IT team at SLAC National Accelerator Laboratory and take your career to the next level as our AI Specialist! We are seeking a highly skilled and motivated AI Specialist with experience on AWS to join our Cloud Services team. In this role, you will design, build, deploy, and operationalize AI/ML solutions that drive business value, working closely with cross-functional stakeholders, data engineers, DevOps, and our platform teams (on-prem and cloud).
As an AI Specialist, you will drive innovation, apply best practices in machine learning (ML) and AI, and ensure the successful integration of AI into our cloud environment.
You'll have the chance to collaborate with a talented team of professionals from various disciplines, exchanging ideas and driving initiatives that enable our organization's goals. Your expertise and problem-solving skills will be essential as we optimize performance, scalability, and efficiency.
Your specific responsibilities will include:
Lead the end-to-end development of AI/ML solutions on AWS: from problem definition, data ingestion, feature engineering, model development/training, to deployment and monitoring in production.
Collaborate with business stakeholders, data scientists, software engineers, and platform teams (on-premises + cloud) to translate business requirements into scalable, performant AI solutions.
Design and implement data pipelines, orchestration, model training, evaluation, and deployment leveraging AWS native services (e.g., SageMaker, EC2, S3, Glue, Lambda, Athena, Redshift) and integrate with on-premises or hybrid infrastructure.
Optimize and fine-tune machine learning models (supervised, unsupervised, deep learning, NLP, computer vision) to maximize accuracy, efficiency, and cost-effectiveness.
Deploy AI/ML models into production environments: set up CI/CD, MLOps practices, automated monitoring, model-drift detection, logging, alerting and lifecycle management.
Ensure robust, secure, scalable, compliant architecture of AI systems in a cloud @context (AWS best practices for security, cost optimization, IAM, networking, governance).
Work with DevOps/platform teams to ensure smooth integration of AI workloads into the overall cloud platform, including hybrid on-premises components (given your dual-environment experience).
Provide guidance, mentoring, and best-practice evangelism in AI/ML, cloud architecture, MLOps, and AWS services to other team members and stakeholders.
Stay up to date on new and emerging AI/ML and AWS technologies, evaluate their applicability, and make recommendations for adoption or a proof of concept.
Prepare and deliver technical presentations, documentation, model-explainability reports, and training workshops for diverse audiences (technical and non-technical).
Maintain and uphold ethical AI practices, ensuring model transparency, fairness, accountability, interpretability, and compliance with institutional policies.
To be successful in this position, you will bring:
Bachelor's degree in Information Technology, or a related field, and ten years of increasingly technical work experience, or a combination of education and relevant experience.
Proven experience with AWS services for ML/AI (for example: SageMaker, EC2, S3, Glue, Athena, Lambda, Redshift, etc).
Strong programming skills in Python (and/or R/Java/Scala) and experience with ML/AI frameworks.
Experience with data engineering: data ingestion, cleaning, transformation, feature engineering, large-scale datasets, data warehousing/Hadoop/Spark as applicable.
Experience deploying models into production, establishing ML operational pipelines (CI/CD, monitoring, drift detection, logging), and maintaining them.
Understanding of cloud architecture best practices (AWS), including networking, security (IAM, encryption, VPC, roles), cost optimization, and performance tuning.
Strong analytical and problem-solving skills, with the ability to work in cross-functional teams and interact with stakeholders at various levels.
Excellent communication and documentation skills ¿ ability to explain complex technical concepts to business and technical audiences.
Demonstrated self-learning and adaptability in fast-moving AI/ML and cloud environments.
SLAC employee competencies:
Effective Decisions: Uses job knowledge and solid judgment to make quality decisions in a timely manner.
Self-Development: Pursues a variety of venues and opportunities to continue learning and developing.
Dependability: Can be counted on to deliver results with a sense of personal responsibility for expected outcomes.
Initiative: Pursues work and interactions proactively with optimism, positive energy, and motivation to move things forward.
Adaptability: Flexes as needed when change occurs and maintains an open outlook while adjusting and accommodating changes.
Communication: Ensures effective information flow to various audiences and creates and delivers clear, appropriate written, spoken, and presented messages.
Relationships: Builds relationships to foster trust, collaboration, and a positive climate to achieve common goals.
Physical requirements and Working conditions:
Consistent with its obligations under the law, the University will provide reasonable accommodation to any employee with a disability who requires accommodation to perform the essential functions of their job.
Given the nature of this position, SLAC is open to on-site, hybrid, and remote work options.
Requires occasional work during extended hours for some activities, such as monthly and quarterly system patching, and during weekend hours for major projects¿ transition to production.
Available for on-call work (rare).
Work standards:
Interpersonal Skills: Demonstrates working well with SLAC colleagues, clients, and external organizations.
Promote Culture of Safety: Demonstrates commitment to personal responsibility and value for environment, safety, and security; communicates related concerns; uses and promotes safe behaviors based on training and lessons learned. Meets the applicable roles and responsibilities as described in the ESH Manual, Chapter 1¿General Policy and Responsibilities: http://www-group.slac.stanford.edu/esh/eshmanual/pdfs/ESHch01.pdf
Subject to and expected to adhere to all applicable University policies and procedures, including but not limited to the personnel policies and other policies found in the University's Administrative Guide, http://adminguide.stanford.edu
As a national laboratory, SLAC National Accelerator Laboratory is responsible for adhering to the Homeland Security Presidential Directive 12 (HSPD-12) and Department of Energy (DOE) Order 473.1A, which require employees to obtain and maintain a HSPD-12 Personal Identity Verification (PIV) Credential. To obtain this credential, employees must successfully complete the applicable tier of federal background investigation post hire and receive a favorable federal adjudication. The tier of federal background investigation will be determined by job duties and national security or public trust responsibilities associated with the job. All tiers of investigation include a declaration of illegal drug activities, including use, supply, possession, or manufacture within the last 1 to 7 years (depending on the applicable tier of investigation). Illegal drug activities include marijuana and cannabis derivatives, which are still considered illegal under federal law, regardless of state laws.
Classification Title: System Administrator 4
Grade: M Job code: 4834
Duration: Regular Continuing
The expected pay range for this position is $190,577 - $213,583 per annum.
SLAC National Accelerator Laboratory/Stanford University provides pay ranges representing its good faith estimate of the salary or hourly wage the university reasonably expects to pay for a position upon hire. The pay offered to a selected candidate will be determined based on factors such as (but not limited to) the scope and responsibilities of the position, the qualifications of the selected candidate, departmental budget availability, internal equity, geographic location, and external market pay for comparable jobs.
At SLAC/Stanford, base pay represents only one aspect of the comprehensive rewards package.
SLAC National Accelerator Laboratory is an Affirmative Action / Equal Opportunity Employer and supports diversity in the workplace. All employment decisions are made without regard to race, color, religion, sex, national origin, age, disability, veteran status, marital or family status, sexual orientation, gender identity, or genetic information. All staff at SLAC National Accelerator Laboratory must be able to demonstrate the legal right to work in the United States. SLAC is an E-Verify employer.
