Our Purpose
At Fiddler, we understand the implications of AI and the impact that it has on human lives. Our company was born with the mission of building trust into AI.
With the rise of the internet, trust in AI has been degraded by a plethora of issues like spam, fraudulent transactions, hate speech, and online abuse.
Fiddler enables organizations to get ahead of these issues by building trustworthy, transparent, and explainable AI solutions.
Fiddler partners with AI-first organizations to help build a long-term framework for responsible AI practices, which, in turn, builds trust with their user base.
Data Science, MLOps, and business teams use Fiddler AI to monitor, explain, analyze, and improve their AI solutions to identify performance gaps, mitigate bias, and drive better outcomes.
Our platform enables engineering teams and business stakeholders alike to understand the why and how behind model outcomes.
Our Founders
Fiddler AI is founded by Krishna Gade (engineering leadership at Facebook, Pinterest, Twitter, and Microsoft) and Amit Paka (two-time founder with acquisitions by Samsung and PayPal and product roles at Expedia and Microsoft).
We are backed by Insight Partners, Lightspeed Venture Partners, and Lux Capital.
Why Join Us
Our team is motivated to unlock the AI opaque box and help society harness the power of AI. Joining us means you get to make an impact by helping reduce algorithmic bias and ensure that models in production across many different industries are transparent and ethical.
We are an early-stage startup and have a rapidly growing team of intelligent and empathetic doers, thinkers, creators, builders, and everyone in between.
The AI and ML industry has a rapid pace of innovation and the learning opportunities here are monumental. This is your chance to be a trailblazer.
Fiddler is recognized as a pioneer in the field of AI Observability and has received numerous accolades, including : 2022 a16z Data50 list, 2021 CB Insights AI 100 most promising startups, 2020 WEF Technology Pioneer, 2020 Forbes AI 50 most promising startups of 2020, and a 2019 Gartner Cool Vendor in Enterprise AI Governance and Ethical Response.
By joining our brilliant (at least we think so) team, you will help pave the way in the AI Observability space.
The Opportunity
In this role, you will be able to make a real impact on the safety of large language models and generative AI solutions across different verticals.
You will work on the cutting edge of envisioning and building new types of tools and algorithms to monitor, explain, and improve such models.
What You'll Do
- Develop and tune novel ML models, metrics and other techniques to classify and explain ML models and LLM prompts / responses
- Setup processes around model building, benchmarking, deployment and MLOps to ensure health and performance of these artifacts in production
- Develop new types of metrics and evaluation methods for quality and robustness of ML models
- Design enterprise-grade, scalable APIs and frameworks to run analysis and validation of customers’ ML models and workflows
- Work with product and customer facing teams to enhance and expand our product
- Recommend and implement engineering best practices, improve the functionality of existing software, and ensure that the design, application, and maintenance of software meets quality standards
- In this role, you will be able to make a real impact on the safety of large language models and generative AI solutions across different verticals.
You will work on the cutting edge of envisioning and building new types of tools and algorithms to monitor, explain and improve such models
What We're Looking For
- BS / MS / PhD in Computer Science, Data Science or equivalent
- 2+ years of experience
- Proficiency with Python
- Experience working with, monitoring and tuning Large Language models in production. Experience with common LLM frameworks (Langchain, Llamaindex, RAG, HuggingFace, BERT models, and eval frameworks like Ragas or Presidio) and MLOps best practices
- Experience debugging and troubleshooting production systems. Experience in designing, consuming and debugging REST APIs and working with common distributed systems infrastructure : Redis, Postgres, RabbitMQ, Celery, Flask
- Excellent organizational, communication, writing and interpersonal skills; also people who are excited by collaboration and teamwork
- You invest in staying up to date with the LLM space, you regularly educate yourself on new capabilities, market trends and needs and are involved in local user groups and / or events relating to LLMs
- Curiosity, ownership, empathy towards customers, willingness to learn new things, and desire to inspire others
Nice to Have
- Experience running and self-hosting LLMs
- Familiarity with any of model explainability, data drift, algorithmic fairness, pattern mining, and model robustness
- Knowledge of infrastructure management (AWS / Google Cloud, Kubernetes, or equivalent on-premises technologies)
- Experience building large-scale distributed systems and working with columnar and vector databases
Pay Range in San Francisco California is $130,000 - $180,000. Hybrid with at least 2 days a week in the Palo Alto office.
The posted range represents the expected salary range for this job requisition and does not include any other potential components of the compensation package, benefits, and perks previously outlined.
Ultimately, in determining pay, we'll consider your experience, leveling, location, and other job-related factors.
Fiddler is proud to be an equal-opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees.
Make sure to apply with all the requested information, as laid out in the job overview below.
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Remote working / work at home options are available for this role.
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