Software Engineer III– AI / Multimodal ML
Location: Fully Remote (EST Preferred)
Pay Rate: $95/hr (W2)
Duration: 12-month contract possible extension/conversion
Schedule: 40 hours/week, Monday–Friday (No overtime)
Benefits: Medical, Dental, Vision, 401(k), Paid Vacation, and Sick Leave

Job Overview:

Our client is seeking an experienced AI Engineer to join its Fundamental AI Research (FAIR) organization—one of the teams driving breakthroughs in next-generation artificial intelligence. In this role, you'll help shape the future of multimodal AI, building the data engines, evaluation frameworks, and annotation platforms that power frontier Multimodal Large Language Models (MLLMs). You'll work at the intersection of research and production, transforming raw image, video, audio, and text data into high-quality datasets and benchmarks that enable cutting-edge AI advancements at scale. This is an opportunity to collaborate with world-class researchers and engineers, leverage massive compute and data resources, and help bring research innovations to products used by billions of people worldwide.

Key Responsibilities:

• Design and curate human- and model-generated datasets for training and evaluating MLLMs across image, video, audio, and text modalities.
• Develop and execute frontier model evaluations, implementing industry-standard metrics and benchmarking methodologies.
• Leverage MLLMs to bootstrap, augment, and rebalance datasets to improve model performance and coverage.
• Fine-tune models using labeled datasets and evaluate model quality across various tasks.
• Build and ship annotation tools and internal data-heavy applications using React and TypeScript.
• Develop secure, scalable data ingestion pipelines capable of processing data from warehouses, warm storage, and flat files.
• Partner closely with researchers, scientists, and engineers to translate research ideas into robust, production-ready systems.

Required Qualifications:

• 5–10+ years of hands-on experience building multimodal datasets, implementing ML evaluation frameworks, and developing production-grade data or annotation tools.
• Strong understanding of ML/AI fundamentals, including:
• Fine-tuning techniques (SFT, preference optimization)
• Prompt engineering
• Model-based evaluation methodologies
• Common failure modes and limitations of LLMs/MLLMs
• At least 1 year of direct experience working with multimodal AI, including image, video, audio, and text datasets.
• Strong Python programming skills and experience with ML frameworks such as PyTorch and the Hugging Face ecosystem.
• Experience running training, inference, or sampling jobs on real-world infrastructure.
• Production experience building web applications using React and TypeScript, with a focus on intuitive internal tools and annotation interfaces.
• Strong data engineering skills, including:
• SQL
• Large-scale data movement
• Batch processing
• Idempotent deduplication
• Parallelization and retry mechanisms
• Experience working in mid-sized technology companies.
• Bachelor's degree in computer science, Engineering, or another quantitative field.

Preferred Qualifications:

• Master's or PhD in AI, Machine Learning, Computer Science, or a related field.
• Research experience in Multimodal Large Language Models (MLLMs), demonstrated through publications or significant project contributions.
• Active open-source contributions, including experience maintaining or contributing to public repositories.

Pursuant to the California Fair Chance Act, Los Angeles County Fair Chance Ordinance for Employers, Los Angeles Fair Chance Initiative for Hiring Ordinance, and San Francisco Fair Chance Ordinance, qualified applicants will be considered for assignment with arrest and conviction records. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness, meet client expectations, standards, and accompanying requirements, and safeguard business operations and company reputation.

#TMN