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Software Engineer Ai Model Training Jobs (NOW HIRING)

Pika

Software Engineer, AI Infra

Palo Alto, CA · On-site

$250K - $350K/yr

... training and serving state-of-the-art AI models * Architect and optimize high-throughput, low ... Strong experience (5+ years) as a software engineer working on systems infrastructure, including ...

Orbifold AI

Research Engineer (Los Altos)

Los Altos, CA · On-site

$250K/yr

Experiment with SOTA models and data curation techniques to maximize AI training efficiency and ... Industries Software Development Referrals increase your chances of interviewing at Orbifold AI by ...

Gallatin AI, Inc

AI Software Engineer

El Segundo, CA · On-site

$80K - $210K/yr

About the Role We're looking for an AI/ML Software Engineer to play a foundational role in ... Establish scalable MLOps pipelines and real-time inference services to streamline model training ...

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Software Engineer Ai Model Training information

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$63.5K

$147.5K

$205.5K

How much do software engineer ai model training jobs pay per year?

As of Aug 20, 2026, the average yearly pay for software engineer ai model training in the United States is $147,524.00, according to ZipRecruiter salary data. Most workers in this role earn between $120,000.00 and $173,000.00 per year, depending on experience, location, and employer.

What does a software engineer AI model training do?

A Software Engineer specializing in AI Model Training is responsible for designing, developing, and optimizing machine learning models. Their work involves preparing and processing large datasets, selecting appropriate algorithms, implementing training pipelines, and evaluating model performance. They collaborate closely with data scientists and other engineers to ensure that AI models are accurate, efficient, and suitable for deployment in real-world applications. Additionally, they may help maintain infrastructure for model training and contribute to research and development of new AI techniques.

What are the key skills and qualifications needed to thrive as a software engineer AI model training?

To excel as a Software Engineer in AI Model Training, you need strong programming skills (especially in Python), a solid grasp of machine learning fundamentals, and typically a degree in computer science or a related field. Experience with frameworks like TensorFlow or PyTorch, familiarity with data processing tools, and sometimes certifications in AI or ML are highly valuable. Analytical thinking, problem-solving, and effective collaboration enhance your ability to develop and refine complex AI models. These skills ensure that AI solutions are robust, scalable, and aligned with organizational goals in a rapidly evolving technological landscape.

What are some common challenges faced by software engineers AI model training, and how can they be addressed?

Software Engineers focusing on AI model training often encounter challenges such as managing large datasets, ensuring data quality, and optimizing model performance. Addressing these issues typically involves close collaboration with data scientists, domain experts, and DevOps engineers to streamline the data pipeline and refine training processes. Staying up to date with the latest advancements in machine learning frameworks and tools can also help overcome technical hurdles. Regular code reviews and cross-functional meetings further support problem-solving and foster a productive work environment.

What is the difference between Software Engineer Ai Model Training vs Data Scientist?

AspectSoftware Engineer Ai Model TrainingData Scientist
Required CredentialsBachelor's in CS, related field; experience with ML frameworksBachelor's or higher in CS, statistics, or related field; strong analytical skills
Work EnvironmentDevelopment teams, AI labs, cloud platformsData analysis, research environments, business units
Employer & Industry UsageTech companies, AI startups, research institutionsTech firms, finance, healthcare, consulting

While both roles involve working with data and machine learning, Software Engineer Ai Model Training focuses on developing and optimizing AI models through coding and engineering practices. Data Scientists analyze data, build models, and generate insights. The roles often collaborate but differ in their core responsibilities and skill sets.

Can I get paid to train AI models?

Yes, software engineers and AI specialists can be paid to train AI models, especially in roles that involve developing, fine-tuning, and optimizing machine learning algorithms. These positions often require knowledge of programming languages like Python, experience with machine learning frameworks, and access to computational resources. Compensation varies based on experience, location, and the complexity of the models being trained.

How to become a software engineer AI model trainer?

To become a software engineer AI model trainer, you should have a strong background in computer science, programming skills in languages like Python, and experience with machine learning frameworks such as TensorFlow or PyTorch. Gaining knowledge in data preprocessing, model evaluation, and working with large datasets is essential, along with relevant certifications or advanced degrees in AI or related fields.
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Software Engineer Ai Model Training jobs near you
Infographic showing various Software Engineer Ai Model Training job openings in the United States as of August 2026, with employment types broken down into 1% As Needed, 82% Full Time, 16% Part Time, and 1% Contract. Highlights an 89% Physical, 1% Hybrid, and 10% Remote job distribution, with an average salary of $147,524 per year, or $70.9 per hour.

Software Engineer, AI Infra

Pika

Palo Alto, CA • On-site

$250K - $350K/yr

Full-time

Re-posted 4 days ago

Job description

About the Role
We are looking for a Staff/Lead Software Engineer, AI Infrastructure, to play a critical role in building and scaling the core infrastructure that powers Pika's AI capabilities. In this position, you will lead the design and implementation of GPU infrastructure, AI model serving APIs, and general AI infrastructure execution-enabling cutting-edge machine learning features that drive our products.
You will be responsible for architecting robust, distributed systems optimized for high-performance AI workloads, large-scale GPU orchestration, and low-latency, reliable API serving. Your work will directly impact the way users experience and interact with generative AI at scale. As a senior technical leader, you'll also mentor engineers, drive best practices, and set the technical vision for AI infrastructure at Pika.
What You'll Do
  • Design, develop, and maintain scalable GPU infrastructure for training and serving state-of-the-art AI models
  • Architect and optimize high-throughput, low-latency APIs for AI model serving and inference
  • Lead the orchestration, scheduling, and efficient utilization of heterogeneous GPU resources across clusters
  • Build and support robust systems for model deployment, monitoring, scaling, and reliability in production environments
  • Collaborate with ML, backend, and platform engineering teams to deliver seamless AI-powered product features
  • Drive technical direction, code reviews, and mentorship across the AI Infrastructure team

What We're Looking For
  • Strong experience (5+ years) as a software engineer working on systems infrastructure, including hands-on work with ML serving and GPU orchestration
  • Deep knowledge of distributed systems, Kubernetes (or similar orchestration frameworks), and cloud-native infrastructure (AWS/GCP/Azure)
  • Proven expertise in building and optimizing APIs for large-scale AI model serving (TensorFlow Serving, Triton, TorchServe, or similar)
  • Familiarity with the challenges of high-throughput, scalable GPU fleet management, scheduling, and efficient model execution
  • Proficiency in backend languages such as Python, Go, or C++, and experience optimizing for performance and reliability
  • Ownership mentality and the drive to solve complex problems independently in ambiguous, high-growth environments
  • Excellent communication, collaborative, and mentorship skills

Nice to Have
  • Experience with multi-modal AI model infrastructure (LLMs, generative models, video/image/speech models)
  • Background in building infra for multi-tenant SaaS, enterprise AI/ML platforms, or operational automation at scale
  • Previous startup experience or experience leading high-impact projects through ambiguity and rapid iteration
  • Experience with competitive coding or large-scale distributed computing environments

What We Offer
  • Competitive salary in the AI industry
  • Equity in a rapidly growing team shaping the future of AI
  • Comprehensive health benefits, monthly stipends, and company retreats
  • A supportive and collaborative office culture-everyone builds, ships, and learns together

About Pika
At Pika, we're building the infrastructure that empowers everyone to create videos and express ideas through advanced AI. Our team is passionate about removing technical barriers to creativity, and we thrive on working together to solve hard problems. We're based in Palo Alto, CA, with a collaborative team working in-office 3-5 days a week.

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