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Principal AI Engineer

Overview

We're looking for a full-time Principal AI Engineer to join us in our mission of bringing the ION Factory OS to next-generation hardware builders around the globe. Our newest team member will join First Resonance in Los Angeles, CA (HQ in Downtown).

Are you excited by the opportunity to assist manufacturers working on eVTOLs, rockets, robots, and autonomous vehicles? The most important characteristic of our AI team is their passion for creating impactful, innovative solutions for companies tackling society’s greatest challenges, such as climate change, space exploration, and autonomous transportation.

With this role, you’ll join a diverse team with a wide range of expertise in AI, manufacturing, and cutting-edge technology. We pride ourselves on being fast learners, creative thinkers, and agile executors. While a spur-of-the-moment ping pong tournament is occasionally required, our number one priority is always assisting our ION customers with our manufacturing platform. If you want to play a key role in shaping the future of hardware and Industry 4.0 through AI innovation, we’d love to meet you!

Responsibilities & Duties 

  • Design, implement, and optimize AI models and pipelines for solving complex manufacturing challenges.

  • Build and maintain AI/ML infrastructure to support model development, training, deployment, and monitoring at scale (MLOps).

  • Develop solutions for generative AI use cases, including autonomous procedure generation, anomaly detection, and quality recommendations.

  • Collaborate with data engineering teams to preprocess and transform structured and unstructured data for model training and evaluation.

  • Integrate AI-driven insights and recommendations into customer-facing products, such as ION Analytics and Autoplan.

  • Research and implement the latest advancements in machine learning, deep learning, and generative AI to improve product capabilities.

  • Partner with DevOps to ensure reliability and scalability of AI systems in production, including CI/CD pipelines for models.

  • Leverage cloud platforms (e.g., AWS, Azure, or GCP) for scalable deployment and management of AI/ML workflows.

  • Work directly with customers to understand their needs and translate business challenges into AI-driven solutions.

Minimum Qualifications & Skills

  • 5+ years of experience in AI/ML engineering, with a proven track record of delivering impactful AI solutions.

  • Proficiency in Python, with expertise in AI/ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.

  • Experience designing and deploying AI/ML pipelines with tools like Airflow, Dagster, or equivalent.

  • Hands-on experience with MLOps tools such as MLflow, Kubeflow, or SageMaker.

  • Strong understanding of data preprocessing, feature engineering, and model evaluation techniques.

  • Familiarity with generative AI models (e.g., LLMs, GANs) and their applications.

  • Deep expertise in leveraging cloud services (e.g., AWS SageMaker, Azure OpenAI Studio, etc ) for building AI solutions.

  • Solid knowledge of APIs (including REST and GraphQL) for integrating AI models into applications.

  • Experience with analytics platforms (e.g., Snowflake, BigQuery) for managing training data and real-time predictions.

  • Strong problem-solving skills and ability to translate business needs into AI solutions.

  • Familiarity with compliance standards (e.g., SOC2, GDPR) and ethical AI principles.

  • Experience handling sensitive information (PII, ITAR, etc) in deploying AI technologies and solutions.

Desired Qualifications:

  • Expertise in natural language processing (NLP) and computer vision applications.

  • Experience with edge AI deployment for real-time, low-latency applications.

  • Familiarity with data governance frameworks and best practices.

  • Proficiency in data visualization tools (e.g., Sigma Computing, Tableau) to present AI-driven insights.

  • Experience working with open-source data formats like Parquet or Delta Lake.

  • Customer-facing experience with AI solutions, including gathering requirements and communicating value.

  • Contributions to open-source projects or published research in AI/ML.

Benefits & Perks

  • Health Insurance; medical, vision, dental, & life insurance.

  • Paid Parental Leave.

  • Employee Stock Option Plan.

  • Team outings, group lunches, open office, happy hours.

  • Paid holidays, sick days.

  • Flexible Friday and PTO.

  • 401K.

First Resonance is an equal opportunity employer dedicated to building an inclusive and diverse workforce. 

First Resonance participates in E-Verify. As part of our onboarding process, a new hire's Form I-9 information will be shared with the federal government to confirm they are authorized to work in the U.S.

Pay is based on factors such as (but not limited to) scope and responsibilities of the position, candidate's work experience and skillset, and location. Certain roles may be eligible for incentive compensation, equity and benefits. 

First Resonance accelerates the speed and reliability of hardware development for companies manufacturing the next generation of hardware products. This includes space exploration, electric airplanes, autonomous vehicles, nuclear reactors, robotics, and more. We are a group of software, hardware, and manufacturing engineers that are bringing the best of modern UX and data science to an industry that has been overly rigid in its innovation. We are removing the barriers preventing radical advancement by providing tools to manufacturing engineers and operators to move information more freely, collaborate with their teams more easily, and use the power of data to predict problems and provide insights that result in better hardware quality and delivery.

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Average salary estimate

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$130000K
$180000K

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What You Should Know About Principal AI Engineer, First Resonance

Are you ready to make a profound impact in the realm of AI? First Resonance is seeking a passionate Principal AI Engineer to join our HQ in vibrant Los Angeles, CA! In this pivotal role, you'll be a key player in enhancing our ION Factory OS, enabling the next generation of manufacturers to thrive across a range of groundbreaking industries—from eVTOLs to autonomous vehicles and even rockets. We believe in the power of creativity and innovation, and we're looking for someone with a diverse skill set in AI, manufacturing, and technology. Imagine designing and optimizing AI models that address complex manufacturing challenges and collaborating with data engineers to transform both structured and unstructured data into actionable insights. It's not just about building AI-driven solutions; it's about shaping the future of hardware and Industry 4.0! At First Resonance, we foster a culture of collaboration where ideas flourish and people come together to tackle some of society's most challenging problems. Plus, you've got to love an environment where a casual ping pong tournament can break out amidst the hustle. If you're ready to dive into generative AI use cases like anomaly detection and quality recommendations while working closely with our customers, we can't wait to connect with you!

Frequently Asked Questions (FAQs) for Principal AI Engineer Role at First Resonance
What are the responsibilities of the Principal AI Engineer at First Resonance?

As a Principal AI Engineer at First Resonance, you will be responsible for designing, implementing, and optimizing AI models and pipelines aimed at solving complex manufacturing challenges. You'll also build and maintain AI/ML infrastructure that supports everything from model development to monitoring at scale. Your role includes developing generative AI solutions, collaborating with data engineering teams, and integrating AI-driven insights into customer-facing products like ION Analytics and Autoplan.

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What qualifications are needed to apply for the Principal AI Engineer position at First Resonance?

To be considered for the Principal AI Engineer role at First Resonance, candidates should have 5+ years of experience in AI/ML engineering, demonstrating a track record of impactful AI solutions. Proficiency in Python and expertise in AI/ML frameworks such as TensorFlow or PyTorch are essential. Familiarity with MLOps tools and a strong understanding of data preprocessing and feature engineering techniques are also required.

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How does First Resonance support AI innovation in manufacturing as a Principal AI Engineer?

At First Resonance, innovation is at the heart of what we do. As a Principal AI Engineer, you will not only design AI models but also partner closely with cross-functional teams to implement the latest advancements in machine learning and deep learning. This role empowers you to explore generative AI applications and directly influence the development of industry-leading solutions that drive manufacturing efficiency and productivity.

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What are the benefits of being a Principal AI Engineer at First Resonance?

As a Principal AI Engineer at First Resonance, you'll enjoy a comprehensive benefits package, including health insurance options, paid parental leave, employee stock options, and flexible work schedules. We believe in maintaining work-life balance and fostering an inclusive work environment where team outings, open office setups, and happy hours contribute to our vibrant workplace culture.

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What is the company culture like at First Resonance for a Principal AI Engineer?

The company culture at First Resonance is collaborative, innovative, and inclusive. As a Principal AI Engineer, you'll be welcomed into a team that values creativity and fast learning. We encourage a playful atmosphere, where spontaneous ping pong games can happen alongside serious discussions about AI and manufacturing. Here, every voice matters as we work together to tackle some of society's most pressing challenges.

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Common Interview Questions for Principal AI Engineer
Can you describe your experience with AI/ML frameworks as a Principal AI Engineer?

When discussing your experience with AI/ML frameworks, focus on specific projects you've worked on where you've utilized tools like TensorFlow, PyTorch, or Scikit-learn. Highlight your role in model creation, optimization, and deployment, demonstrating your technical proficiency and the impact of your work on business outcomes.

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How do you approach data preprocessing in AI/ML projects?

Explain your process for data preprocessing, including steps like data cleansing, normalization, and feature selection. Provide examples of how your preprocessing choices improved model performance, and discuss the importance of these techniques in ensuring accurate and reliable AI outcomes.

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What challenges have you faced in AI/ML deployment, and how did you overcome them?

Prepare to discuss specific challenges you've encountered in deploying AI models, such as integration issues, performance scaling, or compliance concerns. Share your strategies for overcoming these challenges, including collaboration with DevOps teams and the use of MLOps tools.

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How do you ensure ethical considerations in AI solutions?

Discuss your understanding of ethical AI principles, including the importance of transparency, fairness, and compliance with standards like GDPR. Provide examples of how you've incorporated these principles into your work, ensuring that your AI solutions are responsible and trustworthy.

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Can you share your experience with cloud platforms for deploying AI solutions?

Describe your familiarity with cloud services like AWS, Azure, or GCP, emphasizing how you've leveraged these platforms for scalable AI solution deployment. Discuss specific services you've used for model training or data storage, and highlight the advantages of using cloud infrastructure in your projects.

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What generative AI techniques have you implemented in previous projects?

Focus on specific generative AI applications you've worked on, such as creating autonomous procedures or anomaly detection systems. Discuss the methodologies you used, the challenges faced, and the value generated for your stakeholders or clients.

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How do you measure the success of AI models post-deployment?

Discuss key performance indicators (KPIs) that are important for assessing the success of AI models. Explain how you monitor model performance over time, the metrics you track, and how you use this data to make iterative improvements or adjustments.

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What is your approach to collaborating with cross-functional teams?

Outline your collaborative approach, highlighting your experience working with data engineers, DevOps, and product managers. Emphasize the importance of clear communication and understanding team objectives to successfully translate business challenges into effective AI-driven solutions.

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How do you stay updated on the latest advancements in AI/ML technologies?

Explain your strategies for keeping up with AI/ML advancements, such as attending conferences, participating in online courses, and engaging with research papers. Share how you apply this knowledge to enhance your work at First Resonance and maintain a competitive edge in the industry.

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Can you discuss a project where you had to gather customer requirements for an AI solution?

Talk about a specific instance where you engaged with customers to understand their challenges and needs. Describe how you translated those requirements into technical specifications for an AI solution, and highlight the importance of customer feedback in the development process.

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To connect and supercharge the builders of the physical world.

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Full-time, on-site
DATE POSTED
January 10, 2025

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