Senior AI Data Engineer

If you're passionate about pushing the boundaries of data engineering and machine learning, we'd love to hear from you. We are on the hunt for a highly skilled Senior AI Data Engineer to operate at the forefront of Data Engineering and Machine Learning Systems. In this critical role, you will craft and oversee sophisticated end-to-end data pipelines that do more than just move and transform data; they enrich it through remote model inference, handling complex asynchronous processes, capacity management, retry and fallback strategies, and throughput optimization.

This isn t your typical ETL role. It requires hands-on experience with distributed inference infrastructure and a deep understanding of system architecture. You will be instrumental in building solutions that power cutting-edge image generation models, evaluating and enhancing visual quality, prompt adherence, identity preservation, and naturalness, driving innovation in AI-driven content creation.

Responsibilities

• AI-Augmented Data Pipelines: Design and maintain AI-augmented, large-scale data pipelines (billions of images) integrating traditional transformations with ML models (classifiers, embeddings, LLMs) for cleaning and annotation.
• Remote Inference Orchestration: Own the systems for remote ML model inference orchestration within pipelines, managing batching, retries, async jobs, and ensuring graceful degradation.
• Feature Pipelines: Build and maintain scalable pipelines for generating, storing, and serving vector embeddings, including nearest-neighbor index management and quality validation.
• Data Curation at Scale: Source, filter, and curate training datasets using a combination of SQL and model-derived signals (e.g., aesthetic scores, NSFW classifiers), owning the end-to-end data flow and maintaining governance, quality, and compliance.
• Additional Responsibilities
• LLM-Assisted Annotation: Design and operate pipelines that use LLMs and vision models for automated annotation of training data, including auditing workflows to measure and improve annotation model performance.
• Tooling & Frameworks: Contribute to shared tooling and frameworks that make it easier for the broader team to build AI-augmented data pipelines, e.g., reusable operators for model invocation, standard patterns for async job management.
  
  

Required Skills

• Advanced SQL & data pipeline expertise. Complex queries, query optimization, pipeline orchestration frameworks (Airflow, Dataswarm, or equivalent).
• Experience integrating ML models into data pipelines. Calling inference endpoints, managing model versions, batching requests, and handling inference failures at scale.
• Proficiency with AI-assisted coding agents (e.g., Copilot, Cursor, Codex). Expected to leverage AI tools as a force multiplier for writing, debugging, and reviewing code, building pipelines faster, and accelerating day-to-day engineering workflows
• Strong verbal and written communication skills, problem-solving ability, and cross-functional collaboration.
  
  

Preferred Skills

• Working knowledge of embeddings and vector representations, like generating, storing, indexing, and querying embeddings (FAISS, Milvus, or equivalent).
• Familiarity with content-understanding models like image classifiers, object detection, OCR, NSFW detection, and aesthetic scoring.
• Experience with LLMs for data tasks like prompt engineering for annotation, data cleaning, or evaluation using LLM APIs.
• Knowledge of generative AI like diffusion models, image generation, and evaluation metrics (FID, CLIP score, etc.).
  
  

Education / Experience

• Bachelor's degree or higher in Computer Science, Data Engineering, Machine Learning, or a related STEM field.
• Minimum 5 years of industry experience in data engineering, ML engineering, or a hybrid role involving both data pipelines and model serving/inference.
• Demonstrated track record of building and operating production data pipelines that invoke ML models at scale.
  
  

Benefits

• 401(k).
• Dental Insurance.
• Health insurance.
• Vision insurance.
• We are an equal-opportunity employer and value diversity, equality, inclusion, and respect for people.
• The salary will be determined based on several factors, including, but not limited to, location, relevant education, qualifications, experience, technical skills, and business needs.
  
  

Additional Responsibilities

• Participate in OP monthly team meetings and participate in team-building efforts.
• Contribute to OP technical discussions, peer reviews, etc.
• Contribute content and collaborate via the OP-Wiki/Knowledge Base.
• Provide status reports to OP Account Management as requested.
  
  

About Us

At OP, we help you harness the power of technology for maximum impact. A technology consulting and solutions company, we offer advisory and managed services, innovative platforms, and staffing solutions across a wide range of fields including AI, cyber security, enterprise architecture, and beyond. For nearly two decades, we ve been challenging the status quo of the consulting industry, serving up fresh, ingenious thinking through a radically lean structure. Together, this strategy delivers unprecedented performance at an unparalleled pace for faster results that propel your business forward.