Top 4763 Operations Packaging Engineer Jobs

LLM Operations Engineer
Health Business Solutions LLC —Remote
- Remote
- Computer science
- Computer Science
- Bachelor of Science
Senior Packaging Engineer (UFOS)
Equity Packaging, Inc. —Minneapolis, MN
- Full-time
- Remote
- 5 years
- Travel
- SharePoint
Quick Apply
Packaging Engineer III
Gilead Sciences —Foster City, CA
- $117,895 - $152,570 a year
- Full-time
- 5 years
- Mid-level
- Master's degree
- Health insurance
- Dental insurance
Packaging Engineer
Rodan and Fields Beauty, LLC —San Ramon, CA
- $84,000 - $105,000 a year
- Full-time
- Hybrid work
- Mid-level
- Office
- Mentoring
- Paid parental leave
- Health savings account
Packaging Engineer (R3-R4)
Eli Lilly —Indianapolis, IN
- $113,360 - $130,364 a year
- Full-time
- Mid-level
- 3 years
- Travel
- Health insurance
- Dental insurance
Junior Packaging Engineer
Kitsch LLC —Los Angeles, CA
- Full-time
- Hybrid work
- 1 year
- Communication skills
- Entry level
Packaging Engineer
International Flavors & Fragrances —Clackamas, OR
- $91,744 - $114,680 a year
- Full-time
- Background check
- Pass drug screening
- Mid-level
Packaging Engineer I
Exelixis, Inc. —Alameda, CA
- $75,000 - $106,500 a year
- Email
- Analysis skills
- Bachelor's degree
- Travel
- Paid holidays
- Disability insurance
Entry Level Process Engineer
The Dennis Group —Carlsbad, CA
- Up to 50% travel
- Construction site
- Research
- Profit sharing
- Disability insurance
Quick Apply
Packaging Engineer II
Gilead Sciences —Foster City, CA
- $102,085 - $132,110 a year
- Full-time
- Mid-level
- Master's degree
- 2 years
- Health insurance
- Dental insurance
Packaging Engineer
ExoTerra Resource, LLC —Littleton, CO
- $105,000 - $125,000 a year
- Full-time
- Mid-level
- 3 years
- Health insurance
- Paid time off
Quick Apply
Packaging Engineer
GrayMatter Partners, LLC —Columbus, OH
- $100,000 - $130,000 a year
- Full-time
- 7 years
- Engineering
- Bachelor's degree
- Health insurance
- Dental insurance
Quick Apply
Packaging Line Engineer
Vizor —Old Bridge, NJ
- Part-time
- Mid-level
- Continuous improvement
- Flexible schedule
Quick Apply
Engineer, Packaging
Lonza —Tampa, FL
- Full-time
- Engineering
- Mid-level
- 3 years
- Health insurance
- Dental insurance
9d
Engineer I
Opus Plastics Llc —Branchburg, NJ
- $60,000 - $70,000 a year
- Full-time
- US work authorization
- In-person
- 1 year
- Paid time off
Quick Apply
Big Data Engineer
AdvanSix —Remote
- $104,600 - $156,800 a year
- Full-time
- Remote
- System design
- SQL
- Senior level
- Health savings account
- Paid holidays
Quick Apply
Operations Packaging Engineer
Evergen —Alachua, FL
- $65,000 - $80,000 a year
- Full-time
- Mid-level
- Office
- Microsoft Office
Quick Apply
Packaging Engineer
Autumn Harp Inc. —Essex Junction, VT
- $65,000 - $75,000 a year
- Full-time
- Mid-level
- Bachelor's degree
- Experience equivalent to degree accepted
Quick Apply
Manufacturing Engineer
NEFAB PACKAGING WEST LLC —Newark, CA
- $70,000 - $85,000 a year
- Engineering
- ERP systems
- Data analysis skills
- Paid holidays
- 401(k)
Quick Apply
SIM Operations Engineer
Modern Technology Solutions, Inc —Edwards AFB, CA
- 5 years
- Engineering
- Windows
- Disability insurance
- Health insurance

I want to receive the latest job alert for Operations Packaging Engineer

By signing in to your account, you agree to SimplyHired's Terms of Service and consent to our Cookie and Privacy Policy.

Explore jobs in more locations

Operations Packaging Engineer jobs near

LLM Operations Engineer

Health Business Solutions LLC -
Remote

Apply Now

Job Details

Qualifications

AI models
Data integrity assurance
Databricks
Data validation techniques
Spark
AI platforms (beyond public GPTs)
SQL
Machine intelligence
Data quality monitoring
Data-driven problem-solving
DevOps automation
Batch data processing
Python
MLOps
Database software proficiency

Full Job Description

We are looking for an LLM Ops Engineer with deep Databricks experience to build, automate, and scale our machine learning delivery pipelines on the Lakehouse. You’ll own the model lifecycle end‑to‑end—from data ingestion and feature engineering to CI/CD, deployment, monitoring, and governance—ensuring our ML systems are reliable, auditable, secure, and cost‑efficient.

You will partner closely with Leadership, Data Engineers, and subject matter experts to productionize models using Databricks (Delta Lake, Unity Catalog, MLflow, Feature Store, Workflows) and modern DevOps practices across our cloud environments.

Key Responsibilities

Lakehouse & Databricks Platform

Design and maintain Databricks workspaces, clusters, SQL Warehouses, cluster policies, and workspace governance (RBAC, SCIM, SSO, secret scopes).
Implement robust data pipelines with Delta Lake (ACID tables, Z‑ordering, OPTIMIZE/VACUUM), Delta Live Tables (DAGs, expectations), and Workflows (jobs, task orchestration).
Set up Unity Catalog for cross-workspace governance: data & model lineage, permissions, catalogs/schemas, data tags, and auditability.
Operationalize ML models using MLflow (tracking, artifacts, metrics, model registry, approvals, stages: Staging/Production).
Build/maintain Feature Store entities and feature pipelines; enforce reproducibility and feature governance.
Establish model deployment patterns (batch scoring, streaming, microservices) using Model Serving.
Create scalable CI/CD for notebooks, repos, and jobs using Azure DevOps, including unit/integration tests, data/feature validation, and registry promotions.
Implement data quality and ML quality controls (e.g., Great Expectations/Delta expectations, statistical tests, drift detection, canary releases).
Build robust monitoring & alerting for data freshness, pipeline SLAs, model performance, drift, and operational metrics.
Optimize performance and cost (autoscaling, spot instances, DBR runtimes, caching, storage tiers).
Enforce compliance and security best practices (PII handling, encryption at rest/in transit, network controls, secret management).
Partner with data engineers and subject matter experts to standardize templates for experiments, pipelines, model packaging, and deployment.
Document patterns and build internal tooling (CLI utilities, Python packages) to streamline model release and observability.
Contribute to incident response, post‑mortems, and continuous improvements.

ML Lifecycle & MLOps

Operationalize ML models using MLflow (tracking, artifacts, metrics, model registry, approvals, stages: Staging/Production).
Build/maintain Feature Store entities and feature pipelines; enforce reproducibility and feature governance.
Establish model deployment patterns (batch scoring, streaming, microservices) using Model Serving.
Create scalable CI/CD for notebooks, repos, and jobs using Azure DevOps, including unit/integration tests, data/feature validation, and registry promotions.
Implement data quality and ML quality controls (e.g., Great Expectations/Delta expectations, statistical tests, drift detection, canary releases).
Build robust monitoring & alerting for data freshness, pipeline SLAs, model performance, drift, and operational metrics.
Operationalize ML models using MLflow (tracking, artifacts, metrics, model registry, approvals, stages: Staging/Production).
Build/maintain Feature Store entities and feature pipelines; enforce reproducibility and feature governance.
Establish model deployment patterns (batch scoring, streaming, microservices) using Model Serving.
Create scalable CI/CD for notebooks, repos, and jobs using Azure DevOps, including unit/integration tests, data/feature validation, and registry promotions.
Implement data quality and ML quality controls (e.g., Great Expectations/Delta expectations, statistical tests, drift detection, canary releases).
Build robust monitoring & alerting for data freshness, pipeline SLAs, model performance, drift, and operational metrics.
- Design, deploy, and operate LLMOps pipelines for Retrieval‑Augmented Generation (RAG), including document ingestion, embedding generation, vector storage, retrieval strategies, prompt/version management, and evaluation, using Databricks (Delta Lake, MLflow, Model Serving) to ensure secure, auditable, and production‑grade GenAI systems.

Infrastructure & Security

Optimize performance and cost (autoscaling, spot instances, DBR runtimes, caching, storage tiers).
Enforce compliance and security best practices (PII handling, encryption at rest/in transit, network controls, secret management).

Collaboration & Process

Partner with data engineers and subject matter experts to standardize templates for experiments, pipelines, model packaging, and deployment.
Document patterns and build internal tooling (CLI utilities, Python packages) to streamline model release and observability.
Contribute to incident response, post‑mortems, and continuous improvements.

Qualifications

Required

BS/MS in Computer Science, Engineering, Data Science, or equivalent practical experience.
3+ years of MLOps/ML Engineering/Platform Engineering experience in Databricks.
Hands‑on expertise with Databricks: Delta Lake, Unity Catalog, MLflow (Tracking/Registry), Feature Store, Workflows/Jobs, Repos, and Model Serving.
Strong Python engineering skills (packaging, testing, virtual environments); familiarity with Spark (PySpark) and SQL.
Experience with CI/CD (GitHub Actions/Azure DevOps/GitLab), artifact registries, and environment management.
Solid understanding of data/machine learning pipeline design (batch/streaming), data quality checks, and ML evaluation/monitoring.

Soft Skills

Excellent communication and organizational abilities.
Ability to work independently and as a part of cross-functional teams.
Comfortable operating in a fast-paced, changing environment.
Strong analytical and problem-solving skills, with the ability to interpret data and drive recommendations.

HBiz Approval & Disclaimer

This job description is intended to describe the general nature and level of work performed by individuals assigned to this position. It is not intended to be an exhaustive list of all duties, responsibilities, or qualifications required. Responsibilities may change based on business needs, client requirements, or operational priorities.

HBiz reserves the right to modify this job description at any time, with or without notice.

Employment with HBiz is at-will, meaning either the employee or the company may terminate employment at any time, with or without cause or notice, subject to applicable law.

HBiz is an Equal Opportunity Employer and is committed to providing a workplace free from discrimination and harassment. We celebrate diversity and are committed to creating an inclusive environment for all employees.

Apply Now

Refine Your Search

Operations Packaging Engineer jobs

LLM Operations Engineer

Senior Packaging Engineer (UFOS)

Packaging Engineer III

Packaging Engineer

Packaging Engineer (R3-R4)

Junior Packaging Engineer

Packaging Engineer

Packaging Engineer I

Entry Level Process Engineer

Packaging Engineer II

Packaging Engineer

Packaging Engineer

Packaging Line Engineer

Engineer, Packaging

Engineer I

Big Data Engineer

Operations Packaging Engineer

Packaging Engineer

Manufacturing Engineer

SIM Operations Engineer

I want to receive the latest job alert for Operations Packaging Engineer

Related Searches

Explore jobs in more locations

Job Seeker Tools

Employer Tools

Browse

Stay Connected