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Contract Apple Machine Learning Engineer Jobs in Goleta, CA

AppFolio

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site

$112K - $154K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio, Inc.

Sr. Machine Learning Engineer

Santa Barbara, CA · On-site +1

$116K - $159K/yr

Who We Are Looking For We're hiring a Senior Machine Learning Engineer to design and ship the next generation of voice and conversational AI agents within Realm-X. This role helps define AppFolio ...

AppFolio

Staff Machine Learning Engineer

Goleta, CA · On-site

Who We Are Looking For We're hiring a Staff Machine Learning Engineer to help move forward the ML platform that every AI initiative at AppFolio depends on -- training, fine-tuning, inference, RAG ...

Toyon

Deep Learning Algorithm Developer

Goleta, CA

$120K - $200K/yr

Toyon has openings for researchers and developers to solve challenging real-world problems using Artificial Intelligence (AI) / Machine Learning (ML) techniques. Experience in Computer Vision is ...

Toyon

AI/ML Software Engineer

Goleta, CA

$120K - $200K/yr

Toyon is seeking highly qualified AI/ML Software Engineer candidates to develop software in the Python or C++ languages in support of Artificial Intelligence (AI) / Machine Learning (ML) applications.

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Contract Apple Machine Learning Engineer information

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$34K

$138.9K

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How much do contract apple machine learning engineer jobs pay per year?

As of Aug 22, 2026, the average yearly pay for contract apple machine learning engineer in Goleta, CA is $138,937.00, according to ZipRecruiter salary data. Most workers in this role earn between $109,500.00 and $167,200.00 per year, depending on experience, location, and employer.

What is a contract Apple machine learning engineer?

Contract Apple Machine Learning Engineers are professionals hired on a temporary or project basis to develop and implement machine learning models and algorithms specifically for Apple’s products and platforms. They typically work on tasks such as optimizing machine learning workflows for iOS, macOS, or other Apple technologies, and may collaborate closely with Apple’s in-house teams. Their responsibilities can include data preprocessing, model training, evaluation, and integration into Apple’s ecosystem. These engineers are expected to have expertise in machine learning frameworks, programming languages like Python or Swift, and a strong understanding of Apple’s development tools. Contract roles often provide flexibility but may require quick adaptation to Apple’s proprietary systems and high standards.

What are the key skills and qualifications needed to thrive as a contract Apple machine learning engineer?

To thrive as a Contract Apple Machine Learning Engineer, you need a strong background in computer science, mathematics, and deep learning, typically with a relevant degree and experience in building ML models. Proficiency with Python, TensorFlow or PyTorch, Apple's Core ML framework, and version control systems is commonly required. Strong problem-solving skills, collaboration, and effective communication help you navigate project requirements and work with cross-functional teams. These skills and experiences are crucial for delivering high-quality, scalable machine learning solutions that align with Apple's standards and rapidly evolving technology needs.

What are the common challenges faced by contract Apple machine learning engineers when integrating ML models into Apple’s ecosystem?

Contract Apple Machine Learning Engineers often encounter challenges such as ensuring seamless integration of machine learning models with Apple’s proprietary platforms like iOS, macOS, or Core ML. Adapting to Apple’s strict security, privacy standards, and performance requirements is essential, as is optimizing models for real-time performance on Apple devices. Collaborating effectively with cross-functional teams—such as software developers, designers, and QA engineers—is crucial to deliver scalable and user-friendly ML features within project timelines.

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Staff Machine Learning Engineer

AppFolio, Inc

Santa Barbara, CA • On-site

$200 - $250/hr

Other

Re-posted 22 days ago

AppFolio rating

7.2

Company rating: 7.2 out of 10

Based on 8 frontline employees who took The Breakroom Quiz

185th of 246 rated software companies

Job description

Staff Machine Learning Engineer – Software Engineering

Locations: Santa Barbara, CA; San Diego, CA; Remote - San Francisco, CA; Remote - Denver, CO.

Overview

We’re building an AI‑native platform for the real estate industry and are looking for a Staff Machine Learning Engineer to advance the ML platform that underpins all of AppFolio’s AI initiatives.

Your Impact
  • ML Platform: Design and operate AppFolio’s ML infrastructure on AWS – ECS, SageMaker, GPU fleets, model serving, autoscaling, and cost controls.
  • Drive AI Cost Discipline: Optimize cost across all AI applications – provider routing, caching, batch vs. real‑time, model-size selection, and inference economics.
  • Multi‑Provider Reliability: Maintain reliable, multi‑provider LLM access across Google, OpenAI, and Anthropic with sensible fallbacks and abstractions.
  • Training & Fine‑Tuning Stack: Build the training and fine‑tuning stack for small language models, including data pipelines, GPU orchestration, and evaluation.
  • Productionize Research: Partner with Voice & Agents and Research ML engineers to harden prototypes into production systems with SLOs, on‑call rotations, and observability.
  • AI Safety & Guardrails: Operate AppFolio’s AI safety and authorization layer – guardrails on AWS, scoped tool permissions, and human‑in‑the‑loop gates for autonomous agent actions.
Qualifications
  • Systems thinker: Think in terms of platforms and long‑term leverage, not just features.
  • Production builder: Built and scaled ML infrastructure in production with meaningful business impact.
  • Ambiguity: Operate effectively in high ambiguity, turning unclear infra problems into clear direction.
  • Owner‑operator: Take ownership with a founder/owner‑operator mindset, act with urgency, and focus on outcomes.
  • Pace: Strong desire to move fast and deliver impact while maintaining sound engineering judgment.
  • Collaboration: Humble, collaborative, low‑ego, and elevate those around you.
  • Sustainability: Value work‑life balance as a foundation for sustained high performance.
  • Reliability mindset: Treat ML infra like any other production system – SLOs, on‑call, observability, postmortems.
Must Have
  • ML infra at scale: Built and operated production ML infrastructure on AWS – ECS, SageMaker, GPUs, autoscaling, and cost controls.
  • Inference platforms: Production experience with model serving for both LLMs and custom models; understands quantization, batching, and routing.
  • Provider breadth: Direct experience integrating with Google (Vertex/Gemini), OpenAI, and Anthropic APIs in production.
  • Training capability: Trained or fine‑tuned language models end‑to‑end; comfortable with deep learning, evaluation, and inference.
  • Cloud‑native engineering: Strong Python, Docker, dependency management, and CI/CD for AI workloads.
  • RAG & agents: Working knowledge of LangChain / LangGraph and modern RAG patterns over structured and unstructured data.
  • Cost optimization: Demonstrated experience reducing unit cost of AI workloads without regressing quality or latency.
  • AI safety & authorization: Hands‑on experience operating AI guardrails, scoped tool permissions, and authorization layers for production AI systems.
Nice to Have
  • Experience training small language models for production use.
  • GPU performance tuning (vLLM, TensorRT, Triton, or similar).
  • Prior staff‑level role at a company with a significant AI infra footprint.
  • Experience with ontology‑driven systems or knowledge graphs supporting AI applications.
  • Contributions to open‑source ML infrastructure or LLM tooling.
Compensation & Benefits
  • Base pay range: $200,000 – $250,000. Additional benefits and bonuses may apply.
  • Regular full‑time employees are eligible for benefits.
Statement of Equal Opportunity

At AppFolio, we value diversity in backgrounds and perspectives. We are a proud Equal Opportunity Employer and welcome applicants of all races, colors, religions, sexes, sexual orientations, gender identifications, national origins, ages, marital statuses, ancestries, physical or mental disabilities, or veteran status.

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