AI Engineer

At Entertainment Partners and Central Casting, we are committed to creating an

environment where every employee is seen, where ideas, thoughts and perspectives

are shared openly, and where fearless innovation is encouraged. Weaving

diversity, equity, and inclusion into who we are will drive our competitiveness

by encouraging creativity and enhanced decision making.

We help to power Oscar-winning films, Emmy-winning shows, and Clio-winning

commercials. Feel the satisfaction of doing work that directly impacts the most

exciting industry in the world. EP is poised to redefine and evolve the

back-office processes of the entertainment community with security at the core

of what we do.

Are you looking for the next opportunity to revolutionize an industry? If so. …

Entertainment Partners (EP) is seeking a Senior Software Engineer specializing

in AI and Machine Learning to join our AI Services organization. This role sits

at the intersection of applied ML engineering, LLM product development, and

production-grade system design. The AI Senior Software Engineer is responsible

for building, training, evaluating, and deploying AI/ML models and agentic

systems that power EP's intelligent product suite — including Rosey

Intelligence, Project Florence, and EP Answers. The ideal candidate brings deep

hands-on expertise in PyTorch, transformer architectures, and the full ML

lifecycle, combined with the software engineering discipline required to ship

reliable AI products at scale in a production entertainment technology

environment.

KEY RESPONSIBILITIES

In addition to the following, other duties may be assigned to meet business

needs.

AI / ML Engineering

* Design, develop, train, fine-tune, and evaluate machine learning models using

PyTorch and associated ecosystem libraries (torchvision, torchaudio,

torch.nn, torch.optim).

* Build and maintain ML training pipelines, experiment tracking workflows, and

model evaluation frameworks.

* Implement transformer-based models and large language model (LLM)

integrations for production use cases including NLP, information extraction,

classification, and generation.

* Apply parameter-efficient fine-tuning techniques (LoRA, QLoRA, PEFT) to adapt

foundation models for EP-specific domains (payroll, residuals, production

management).

* Design and implement RAG (Retrieval-Augmented Generation) architectures using

vector databases (pgvector, Pinecone, Weaviate) and semantic search

pipelines.

* Optimize model inference for latency and throughput; implement quantization,

batching, and caching strategies for production serving.

* Develop and maintain AI evaluation frameworks — including automated evals as

unit tests — to ensure model behavior is reliable, safe, and

production-grade.

LLM Integration & Agentic Systems

* Design and implement LLM-powered agentic workflows using LangChain,

LangGraph, and EP's internal MCP (Model Context Protocol) server

architecture.

* Build multi-step reasoning pipelines, tool-calling agents, and autonomous

task execution systems that integrate with EP's enterprise data and product

APIs.

* Implement prompt engineering strategies, few-shot templates, chain-of-thought

scaffolding, and structured output validation.

* Apply and maintain EP's AI quality engineering (QE) standards including

failure taxonomy, runtime guardrails, and evidence-driven release gates.

* Contribute to EP's Enterprise Context Engine — the governed,

zero-data-retention AI context layer exposed via MCP to Tabnine Agent and

Claude Code.

* MLOps & Production Engineering

* Build and maintain MLOps infrastructure for model training, experiment

tracking (MLflow, Weights & Biases), versioning, and deployment.

* Containerize and deploy ML services using Docker and Kubernetes; integrate

with CI/CD pipelines (GitHub Actions, Azure DevOps).

* Monitor model performance in production; implement drift detection, feedback

loops, and automated retraining triggers.

* Ensure AI systems meet EP's security, privacy, and compliance requirements

including data minimization and access control for sensitive payroll data.

* Collaborate with the data engineering team to design and maintain feature

stores, data pipelines, and training data infrastructure.

Collaboration & Technical Leadership

* Partner with the Chief Architect AI & Data and CAIO to define AI architecture

patterns and best practices for the EP engineering organization.

* Collaborate with product managers, UX designers, and full stack engineers to

translate AI capabilities into well-designed product features.

* Conduct code reviews for AI/ML code with a focus on reproducibility,

correctness, and production readiness.

* Mentor engineers across the organization in AI engineering fundamentals, LLM

integration patterns, and responsible AI practices.

* Stay current with the rapidly evolving AI/ML landscape; evaluate new models,

frameworks, and techniques for potential application at EP.

* Contribute to EP's PE AI Maturity Scorecard (S1–S3) by advancing the

organization's AI capability maturity.

* Represent EP's AI engineering practices in Architecture Review Board

discussions.

JOB REQUIREMENTS / QUALIFICATIONS NEEDED

Minimum qualifications:

* Bachelor's or Master's degree in Computer Science, Machine Learning,

Statistics, Mathematics, or a related quantitative field.

* 6–10+ years of professional software engineering experience, with a minimum

of 3+ years focused on ML/AI engineering in production environments.

* Expert-level proficiency in Python; deep familiarity with the Python ML/AI

ecosystem.

* Hands-on production experience with PyTorch — model definition (nn.Module),

custom training loops, autograd, GPU acceleration (CUDA), and model

serialization (TorchScript, ONNX).

* Experience with Hugging Face Transformers, Datasets, and PEFT libraries;

ability to fine-tune and adapt foundation models.

* Demonstrated experience building RAG pipelines, including chunking

strategies, embedding models, vector store selection, and retrieval

evaluation.

* Production experience integrating LLM APIs (OpenAI, Anthropic, open-source

via vLLM/Ollama) and building reliable prompt engineering systems.

* Experience with LangChain or LangGraph for multi-step agent and tool-calling

workflows.

* Strong understanding of ML fundamentals: supervised/unsupervised learning,

loss functions, regularization, evaluation metrics, and statistical

validation.

* Experience with experiment tracking tools (MLflow, Weights & Biases, Comet)

and reproducible ML workflows.

* Working knowledge of containerization (Docker) and cloud ML services (AWS

SageMaker, Azure ML, or OCI Data Science).

* Experience with SQL and NoSQL databases; ability to design data pipelines for

ML training and inference.

Preferred qualifications:

* Experience with additional deep learning frameworks (TensorFlow, JAX) or

framework interoperability (ONNX).

* Familiarity with computer vision (torchvision, OpenCV) or speech/audio

processing (torchaudio) domains.

* Experience with model compression techniques: quantization (INT8, FP16,

BF16), pruning, distillation.

* Experience serving ML models at scale using Triton Inference Server,

TorchServe, Ray Serve, or similar.

* Contributions to open-source ML projects or published research (papers,

patents, or technical blog posts).

* Experience with responsible AI frameworks, bias evaluation, and AI governance

practices.

* Familiarity with MCP (Model Context Protocol) server development for exposing

tools to AI agents.

* Prior domain experience in payroll, fintech, media, or enterprise SaaS

environments.

* Experience with Kubernetes-based ML workload orchestration (Kubeflow,

KFServing, or similar).

* Hybrid work environment — Burbank, CA headquarters with flexible remote

schedule.

* On-call availability as needed for production AI system incidents and model

deployment events.

* Access to GPU-accelerated compute environments (cloud-based) for model

training workloads.

* Sitting for extended periods of time at a computer workstation.

* Dexterity of hands and fingers to operate a computer keyboard and mouse.

* Occasional participation in early-morning or evening sessions to coordinate

with distributed teams or international partners.

Other benefits and perks included are:

* Health, Dental, and Vision options

* 401(k) retirement savings plan and company match

* Paid holidays, vacation time, and sick time

* Participation in company equity plans

* Employee Assistance Program, mental health and wellness programs

* Training and development

* Annual bonus and merit reviews

The salary range for this position in $140,000 to $180,000 and will be

commensurate with experience related to the position.

Entertainment Partners seeks to employ the most qualified individuals from the

available workforce and to provide equal employment opportunity for all persons.

Our policy prohibits unlawful discrimination based on race, color, religion,

religious creed, sex, gender identity/expression, age, pregnancy, citizenship

status, marital status, national origin or ancestry, physical or mental

disability (whether perceived or actual), medical condition (cancer-related or

genetic characteristics-related), sexual orientation, veteran status,

medical/family care leave status or any other consideration made unlawful by

applicable federal, state, or local laws. Qualified applicants with arrest or

conviction records will be considered for employment in accordance with the Los

Angeles County Fair Chance Ordinance for Employers and the California Fair

Chance Act.

Equal opportunity extends to all aspects of the employment relationship,

including recruiting, hiring, transfers, promotions, training, terminations,

working conditions, compensation, benefits, and other terms and conditions of

employment.