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Feast Jobs (NOW HIRING)

ASM Global

PT Server- Spurs Club

San Antonio, TX

Responsible for setting up and maintaining feast items * Responsible for taking food and beverage orders from guests * Demonstrates a knowledge of menu and or feast items and features * Take food ...

ASM Global

FT Server- Spurs Club

San Antonio, TX · On-site

Essential Job Functions Responsible for setting up and maintaining feast items Responsible for taking food and beverage orders from guests Demonstrates a knowledge of menu and or feast items and ...

AEG

FT Server- Spurs Club

San Antonio, TX · On-site

Essential Job Functions • Responsible for setting up and maintaining feast items • Responsible for taking food and beverage orders from guests • Demonstrates a knowledge of menu and or feast ...

AEG

PT Server- Spurs Club

San Antonio, TX · On-site

Responsible for setting up and maintaining feast items * Responsible for taking food and beverage orders from guests * Demonstrates a knowledge of menu and or feast items and features * Take food ...

EXL

Senior ML Engineer / MLOps Engineer

Passaic, NJ · On-site

$108K - $148K/yr

Implement model lifecycle management practices, including model registries, versioning, and feature stores (e.g., MLflow, Feast), and establish strong observability frameworks using Prometheus and ...

Spicer Rudstrom, PLLC

Associate Attorney

Chattanooga, TN · On-site

$75K - $100K/yr

Consistent, high-quality work (no "feast or famine") * A supportive team that values professionalism and balance * Real opportunity to grow as a litigator--not just push paper * Competitive ...

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Feast information

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$13

$25

$37

How much do feast jobs pay per hour?

As of Jun 16, 2026, the average hourly pay for feast in the United States is $25.44, according to ZipRecruiter salary data. Most workers in this role earn between $17.31 and $33.17 per hour, depending on experience, location, and employer.

What are Feast jobs?

Feast jobs typically refer to roles related to the Feast open-source feature store for machine learning. A Feast job may involve managing, developing, or maintaining the infrastructure that enables the efficient storage, retrieval, and serving of machine learning features. These positions often require knowledge of data engineering, cloud computing, and MLOps practices. Professionals working with Feast collaborate with data scientists and engineers to streamline ML workflows and ensure scalable, reliable access to feature data.

What are the key skills and qualifications needed to thrive as a Feast Coordinator, and why are they important?

To thrive as a Feast Coordinator, you need strong organizational skills, event planning experience, and often a background in hospitality or culinary management. Familiarity with event management software, budgeting tools, and food safety certifications is typically required. Exceptional communication, leadership, and problem-solving abilities help ensure seamless coordination among vendors, staff, and guests. These skills are crucial for delivering memorable, well-executed events that meet client expectations and comply with safety standards.

What are some common challenges faced by professionals working as a Feast event coordinator, and how can they be overcome?

Feast event coordinators often juggle multiple vendors, strict timelines, and high client expectations, which can be challenging, especially during large or themed gatherings. Effective communication, strong organizational skills, and the ability to adapt quickly to last-minute changes are essential for success. Building a reliable network of suppliers and maintaining detailed checklists can help streamline the planning process and reduce stress. Regular team meetings and feedback sessions also ensure everyone is aligned, contributing to a smooth and memorable feast event.
More about Feast jobs
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Feast jobs near you
Infographic showing various Feast job openings in the United States as of June 2026, with employment types broken down into 84% Full Time, 9% Part Time, and 7% Contract. Highlights an 94% Physical, 2% Hybrid, and 4% Remote job distribution, with an average salary of $52,920 per year, or $25.4 per hour.
Principal Software Engineer, AI Platform Engineering

Principal Software Engineer, AI Platform Engineering

Saviynt

El Segundo, CA • On-site

$143K - $192K/yr

Full-time

Posted 19 days ago

Job description

ABOUT SAVIYNT
Saviynt is a leader in identity security, delivering an AI-powered platform that governs and secures access to applications, data, and business processes for global enterprises and government institutions. Built for the AI era, Saviynt helps organizations move faster - securely and compliantly.
ABOUT THE ROLE
You set the architectural direction for how training data flows, evolves, and is governed across the AI Platform. You define the standards ML engineers and scientists build on, and ensure every training signal is tenant-isolated, PII-free, and traceable from source to model.
WHAT YOU'LL OWN
  • AI Data Lake on GCS: bucket layout, raw - silver - gold tier separation, CMEK encryption, lifecycle rules
  • Batch pipelines: Spark on Dataproc for TB-scale feature backfills, Iceberg compaction, and daily S3-GCS incremental sync
  • Streaming pipelines: Apache Beam on Dataflow for sub-5-min CDC ingestion with exactly-once semantics and PII assertion gates
  • Schema registry: Avro / Protobuf schema versioning, compatibility modes, and migration playbooks for safe schema evolution
  • Orchestration: Flyte as primary DAG layer - task authoring standards, domain isolation, retry policies, DataCatalog memoization; evaluate Kubeflow Pipelines where relevant
  • Multi-tenancy: strict per-tenant GCS prefix isolation, quota policies, and cross-tenant contamination validation
  • Data Anonymizer and Data Labeler microservices: strip PII and attach ML labels before signals leave each customer environment
  • Feature store: Feast offline (GCS Parquet) and online (Redis) with point-in-time correctness and < 0.1% consistency SLA
  • Vector database: operate Pgvector (Cloud SQL) for POC and Qdrant on GKE for production-scale embedding storage; design index strategies (IVFFlat, HNSW) and manage ANN query latency SLAs
  • RAG data pipeline: build embedding generation pipelines that chunk, encode, and upsert document embeddings into the vector store; own the data refresh cadence and staleness SLAs for retrieval context
  • Service APIs: expose data platform services (feature serving, embedding upsert, schema validation) over HTTPS with mTLS and gRPC where low-latency streaming is required
  • Synthetic data pipelines for dev/staging where real customer data is not permitted
  • Data quality gates: Great Expectations / dbt checks as Flyte tasks, blocking on schema and PII-absence failures

YOU'LL THRIVE HERE IF YOU HAVE
  • 8+ years of data engineering at production scale across multiple companies
  • Demonstrated principal impact: platform standards you defined adopted org-wide, or major cross-team pipeline/schema migrations you led
  • Data lake ownership (essential): you have designed and operated a production data lake end-to-end - storage layout, partitioning strategy, tiered retention (hot/warm/cold), table format (Iceberg or Delta Lake), compaction, and access control; not just consumed one
  • Deep Spark (PySpark / Scala): executor tuning, shuffle diagnosis, Iceberg table maintenance
  • Hands-on Beam / Dataflow: windowing, exactly-once, side inputs, autoscaling
  • Schema registry experience: Protobuf / Avro compatibility rules, breaking-change migrations in production
  • Orchestration at scale: Flyte, Kubeflow Pipelines, Airflow, or Prefect - operated in production, ideally benchmarked two
  • Multi-tenant data architecture: per-tenant isolation as a hard requirement, not a post-hoc concern
  • Feature store operations: Feast or Tecton, point-in-time joins, online/offline consistency
  • Vector databases: Pgvector or Qdrant in production - index tuning, ANN search, embedding upsert pipelines
  • RAG data fundamentals: chunking strategies, embedding model selection, retrieval quality evaluation, and context freshness management
  • API transport: gRPC and HTTPS/mTLS for service-to-service communication; comfortable defining proto contracts and managing certificate lifecycle
  • Bachelor's degree in Computer Science, Engineering, or a related field, or equivalent practical experience or equivalent military experience

NICE TO HAVE
  • Differential privacy or k-anonymity for ML training datasets
  • Open source contributions: Feast, Great Expectations, Apache Beam, or dbt
  • Familiarity with IAM / access governance data: entitlements, provisioning events, access graphs
  • Iceberg or Delta Lake at petabyte scale

WHY JOIN SAVIYNT
  • Work on a large-scale, Kubernetes-based SaaS platform
  • Solve challenging cloud and reliability problems at scale
  • Collaborate with strong engineers in a reliability-focused culture
  • Competitive compensation, benefits, and growth opportunities

SECURITY & COMPLIANCE
This role requires adherence to Saviynt's information security and privacy policies, including annual security training.
We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.

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