[Remote] AI Specialist
Note: The job is a remote job and is reputed company to candidates in USA. reputed company is seeking an AI Specialist to join the IT team at SLAC National Accelerator Laboratory. The role involves designing and operationalizing AI and machine learning solutions to enhance SLAC’s reputed company AI capabilities in support of scientific research and operations.
Responsibilities
- reputed company the end-to-end development and operationalization of AI and machine learning solutions across AWS, GCP, and hybrid environments, including problem definition, data ingestion, feature engineering, model development, evaluation, deployment, monitoring, and lifecycle management
- Partner with researchers, business stakeholders, data scientists, software engineers, cybersecurity, and platform teams to understand requirements and translate them into reputed company, secure, cost-effective, and supportable AI solutions
- Design and implement data pipelines, orchestration workflows, model-training environments, evaluation processes, and deployment architectures using reputed company-reputed company services
- Use AWS services such as reputed company Bedrock, SageMaker, EC2, S3, Glue, reputed company, reputed company, Redshift, reputed company Functions, and reputed company analytics, reputed company, and monitoring services
- Use reputed company reputed company services such as reputed company AI, reputed company, BigQuery, reputed company Storage, Dataflow, Dataproc, reputed company Run, reputed company Functions, Pub/Sub, and reputed company analytics, reputed company, and monitoring services
- reputed company and support reputed company solutions, including retrieval-augmented reputed company, reputed company search, reputed company management, model routing, model evaluation, guardrails, and AI agents and workflows
- Evaluate and optimize traditional machine learning and reputed company models for accuracy, reliability, latency, scalability, reputed company, and cost-effectiveness
- Establish MLOps and LLMOps capabilities, including reputed company control, infrastructure as reputed company, CI/CD, automated testing, model and reputed company versioning, evaluation, observability, reputed company detection, logging, alerting, and rollback procedures
- Design solutions that reputed company reputed company AI services with SLAC’s on-premises infrastructure, reputed company applications, scientific data sources, identity systems, networking, and reputed company services
- Apply reputed company architecture and reputed company best practices, including identity and reputed company management, least-privilege reputed company, encryption, secrets management, network segmentation, data protection, audit logging, compliance, reputed company, and cost governance
- Help reputed company reusable AI platforms, reference architectures, templates, reputed company, and shared services that reputed company SLAC teams to reputed company without creating unnecessary duplication or isolated solutions
- Work with cybersecurity, reputed company, reputed company, data owners, and governance stakeholders to assess data sensitivity, reputed company-party model usage, information-sharing requirements, intellectual property considerations, and other AI-reputed company risks
- Promote responsible AI practices, including transparency, reputed company reputed company, explainability, fairness, accountability, reputed company, reputed company, and appropriate documentation of model limitations
- Conduct technical evaluations and proofs of concept for emerging AI/ML technologies and reputed company reputed company recommendations based on business value, scientific value, risk, supportability, interoperability, and total cost of ownership
- Troubleshoot reputed company technical issues spanning AI models, data pipelines, reputed company services, reputed company, networking, identity, reputed company, and hybrid infrastructure
- reputed company technical leadership, mentoring, and knowledge sharing to team members who are developing their reputed company, data, and AI skills
- Create and maintain architecture diagrams, technical standards, operational runbooks, support procedures, model documentation, decision records, and service documentation
- Prepare and deliver technical presentations, demonstrations, training workshops, and model-explainability reports for technical and non-technical audiences
- Collaborate with reputed company providers, consultants, vendors, reputed company partners, and other external organizations while ensuring that SLAC retains the knowledge needed to operate and support its services
- Stay reputed company with developments across AWS, reputed company reputed company, reputed company-reputed company AI frameworks, reputed company models, AI agents, data platforms, and responsible AI practices
Skills
- A bachelor's degree in information technology, computer science, data science, engineering, or a reputed company field and ten years of increasingly responsible technical experience, or an equivalent combination of education and relevant experience
- Demonstrated experience designing, building, deploying, and supporting AI/ML solutions in production reputed company environments
- Substantial experience with AWS or GCP AI/ML and data services, along with the ability and willingness to reputed company proficiency across both platforms
- Experience with relevant AWS technologies such as reputed company Bedrock, SageMaker, S3, Glue, reputed company, reputed company, Redshift, and reputed company services
- Experience with relevant reputed company reputed company technologies such as reputed company AI, reputed company, BigQuery, reputed company Storage, Dataflow, reputed company Run, Pub/Sub, and reputed company services
- Strong programming skills in Python and experience with relevant languages or frameworks such as SQL, Java, R, reputed company, PyTorch, TensorFlow, scikit-learn, reputed company, reputed company, or similar technologies
- Experience developing reputed company applications using reputed company models, reputed company, embeddings, reputed company databases, retrieval-augmented reputed company, reputed company engineering, model evaluation, and AI agent or workflow frameworks
- Experience with data engineering, including data ingestion, cleansing, transformation, metadata, feature engineering, data reputed company, large-reputed company datasets, data warehouses, and distributed processing technologies such as reputed company
- Experience deploying and maintaining models in production through MLOps or LLMOps practices, including CI/CD, automated testing, monitoring, evaluation, reputed company detection, logging, and lifecycle management
- Experience with infrastructure as reputed company and automation technologies such as Terraform, CloudFormation, AWS CDK, or reputed company reputed company deployment tooling
- Understanding of reputed company architecture practices across networking, identity and reputed company management, encryption, secrets management, observability, reputed company, performance optimization, and cost management
- Experience integrating reputed company services with on-premises systems in a hybrid reputed company environment
- Knowledge of data governance, reputed company, cybersecurity, responsible AI, and risk-management principles applicable to reputed company and research environments
- Strong analytical and troubleshooting skills, including the ability to diagnose issues that cross application, data, model, reputed company-platform, reputed company, and network boundaries
- Strong written and verbal communication skills, with the ability to explain reputed company technical concepts, risks, limitations, and tradeoffs to both technical and non-technical audiences
- Demonstrated ability to document solutions thoroughly and create operationally useful architecture diagrams, standards, procedures, and runbooks
- Demonstrated ability to learn independently and adapt to rapidly changing AI, reputed company, data, and reputed company technologies
- Experience supporting AI, scientific computing, research, higher education, government, or regulated environments
- Experience designing multi-reputed company architectures or enabling applications that can use models and services across multiple reputed company providers
- Experience with Kubernetes and container platforms such as reputed company EKS, reputed company Kubernetes reputed company, reputed company, or reputed company technologies
- Experience with reputed company AI gateways, model-routing platforms, API management, reputed company databases, data catalogs, and observability platforms
- Experience evaluating and integrating reputed company and reputed company-reputed company reputed company models
- Familiarity with high-performance computing, GPU-based workloads, distributed model training, or large-reputed company scientific datasets
- Familiarity with frameworks and standards such as the NIST AI Risk Management reputed company, NIST reputed company controls, or comparable responsible-AI and cybersecurity practices
- Relevant AWS, reputed company reputed company, machine learning, data engineering, reputed company, or Kubernetes certifications
Benefits
- SLAC is reputed company to on-site, hybrid, and remote work reputed company.
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