DeepRec.ai

AI Engineer

MOUNTAIN VIEW, CAPosted 18 days ago

Job summary

  • Job post source

    This job is from a recruiting firm hiring for a separate company as indicated by 'Our client' and the indirect description of the employer.

  • Job overview

    The AI Engineer role at DeepRec.ai involves developing and maintaining large language model applications to improve AI model performance through a crowdsourced platform.

  • Responsibilities and impact

    The candidate will architect and maintain LLM applications, manage the ML lifecycle, handle data and model design, develop training and evaluation protocols, monitor GenAI trends, and contribute to strategic decisions and innovative AI solutions.

  • Compensation and benefits

    The salary range is $180,000 to $250,000 depending on experience, with a full-time position based in Mountain View requiring 4 days per week onsite; no specific benefits mentioned.

  • Experience and skills

    Requires minimum 3 years ML experience, success deploying scalable AI models, advanced Python skills, proficiency with ML frameworks like PyTorch and TensorFlow, and a relevant degree; PhD and published research preferred.

  • Career development

    Opportunities include working on foundational AI infrastructure, engaging with cutting-edge AI technologies, and contributing to innovative product areas in a startup environment.

  • Work environment and culture

    The company is a well-funded startup backed by top-tier VCs, emphasizing innovation at the intersection of AI, product, and decentralized data with a dynamic engineering team.

  • Company information

    DeepRec.ai is a startup building a crowdsourced platform to benchmark AI models using gamification and blockchain for transparency, aiming to improve AI system reliability.

  • Team overview

    The candidate will join a dynamic engineering team focused on AI model evaluation and product development.

  • Job location and travel

    The position is full-time in Mountain View with a hybrid schedule of 4 days onsite per week.

  • Application process

    Applicants are encouraged to apply if interested in advancing AI and working on consumer AI products; no specific application steps detailed.

  • Unique job features

    The role offers the chance to work on a unique platform combining gamification, user incentives, and blockchain to generate high-quality human preference data at scale for AI fine-tuning.

Company overview

DeepRec.ai is a technology company based in Los Angeles, California, specializing in advanced artificial intelligence and machine learning solutions. The company focuses on computer vision, data science, and predictive modeling to develop cutting-edge technologies. DeepRec.ai makes money by offering high-impact AI solutions and hiring top-tier talent for roles such as data scientists, computer vision engineers, and machine learning scientists. The company also fosters a community of innovators and deep tech enthusiasts through initiatives like the DeepRec.AI Leadership Lab, which aims to decode the future of technology.

How to land this job

  • Position your resume to highlight your expertise in large language model architectures and practical experience deploying generative AI solutions in production, as these are central to the AI Engineer role at DeepRec.ai.

  • Emphasize your skills in Python programming and proficiency with ML frameworks like PyTorch, TensorFlow, NumPy, and JAX, along with your ability to manage the full ML lifecycle and develop MLOps infrastructure.

  • Apply through multiple channels including DeepRec.ai's official careers page and LinkedIn to maximize your chances of being seen by their recruitment team.

  • Connect on LinkedIn with engineers and team members in DeepRec.ai's AI or engineering divisions; start conversations by referencing recent AI trends or their innovative use of blockchain for AI model benchmarking.

  • Optimize your resume for ATS by incorporating keywords such as 'large language models,' 'generative AI,' 'ML lifecycle management,' 'MLOps,' and specific frameworks like 'PyTorch' and 'TensorFlow' to ensure it passes automated screening.

  • Use Jennie Johnson's Power Apply feature to automate tailored applications, identify multiple application portals, and find relevant LinkedIn contacts, allowing you to focus your energy on preparing for interviews and networking effectively.

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