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Appen, based in San Francisco, is seeking a Forward Deployed Engineer to design, deploy, and optimize GenAI data solutions for enterprise clients. You will own data quality across datasets, pipelines, and automations, collaborating with engineering and client teams.
Role requires 3+ years in customer-facing tech, a CS/engineer/data science background, and experience with GenAI/ML workflows. Hybrid SF office presence two days weekly; compensation ranges with base salary and incentives.
Role Purpose
The Forward Deployed Engineer works directly with enterprise clients to design, deploy, and optimize GenAI data solutions, with full ownership of final delivered data quality. Embedded across engineering, data operations, and client delivery, this role ensures datasets, pipelines, workflows, and automations meet defined accuracy, reliability, and performance requirements for GenAI model development.
This is a hybrid role based in San Francisco, CA. You will be required to work from our San Francisco office two days per week.
$150,000 - $200,000 a year
The total target compensation for this full-time role is inclusive of base salary and performance-based incentive. Actual compensation is determined based on role, level, experience and technical expertise. Appen offers a comprehensive benefits package, including medical, dental, and vision coverage, retirement plan options and paid time off.
At Appen, we foster a culture of innovation, collaboration, and excellence. We value curiosity, accountability, and a commitment to delivering the highest-quality AI solutions for frontier models.
You’ll work on complex challenges that shape the future of AI across industries and geographies, alongside talented people in a culture that values humility over ego. You’ll have the flexibility to deliver in a way that works for you and your team, supported by tools, resources and development opportunities to continue to build your capability over time.
Appen has been a leader in AI training data for over 30 years. We specialize in human generated data to train, fine tune, and evaluate models across generative AI, large language models, computer vision, and speech recognition. Our AI assisted data annotation platform and global crowd of more than 1 million contributors in over 200 countries support model pre-training, supervised fine tuning, evaluation and benchmarking, safety and red teaming, and multilingual global expansion.