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AI Engineer

Normal Computing

Normal Computing

Software Engineering, Data Science
New York, NY, USA · Remote
Posted on Thursday, July 4, 2024

Normal Computing. Incredible Opportunities.

At Normal, we're rewriting AI foundations to advance the frontier of reasoning and reliability in the real world. At the center of our mission is bridging artificial intelligence to the most sensitive industrial and advanced manufacturing applications around the globe. We are tackling these problems with a mix of interdisciplinary approaches across the full stack, from probabilistic software infrastructure and algorithms to hardware and physics.

At Normal, we understand that our technology is only as powerful as the people behind it. Every employee drives significant impact within our products, often working directly with customers and embedding across our tightly-knit team. Our team members are driven by curiosity and passion for solving some of the most challenging problems in the physical world.

Join us as we incite a second industrial revolution through AI purpose-built for (and in) the physical world, as part of our incredible team that’s anything but normal.

Your Role in Our Mission:

Are you ready to leverage your AI and machine learning expertise to tackle real-world challenges? We're seeking an AI Engineer to join our team. In this role, you'll be at the forefront of developing and implementing AI-powered solutions that solve complex problems across various industries. You'll work closely with our research scientists, software engineers, and product teams to deliver high-quality, ML-first applications. We welcome candidates of all experience levels, from junior to senior.

Responsibilities:

  • Develop and implement state-of-the-art machine learning models and algorithms to solve complex problems in both semiconductor and industrial sectors.

  • Build and maintain robust data pipelines, including data collection, preprocessing, transformation, and feature engineering.

  • Explore Bayesian and non-Bayesian approaches to reliable deep learning for solving client problems.

  • Set up benchmarking tools and infrastructure to support rapid experimentation and iteration, with a clear path to production deployment.

  • Create client-relevant benchmarks to continually measure quality and robustness of solutions relative to baselines.

  • Architect systems around open source foundation models to process a variety of materials, including multi-modal PDFs, customer service logs, and tabular data

  • Architect AI-powered applications with a focus on handling high latency, variance, and potential errors inherent in working with LLMs.

  • Collaborate with cross-functional teams to integrate AI solutions into our products and services.

  • Stay current with the latest research and industry trends in machine learning and AI.

What Makes You A Great Fit:

  • Proficiency in Python and experience with ML frameworks like PyTorch.

  • Familiarity with AWS SageMaker and deploying ML models from ideation to production.

  • Strong understanding of machine learning algorithms for anomaly detection, predictive analytics, and root cause analysis.

  • Experience and curiosity for Large Language Models (LLMs), Large Multi-modal Models (LMMs).

  • Ability to handle and preprocess large datasets, including time-series and sensor data.

  • Proven track record of building ML methods to power products and solve complex problems.

  • Excellent problem-solving skills and a strategic mindset for identifying valuable solutions.

  • Curiosity and excitement to learn across the company, essential for navigating a startup environment.

  • Transparent and open communication style.

What Elevates Your Application:

  • Experience with cloud platforms like AWS, Google Cloud, or Azure.

  • Familiarity with prompt engineering and fine-tuning of large language models.

  • Knowledge in predictive maintenance, quality control, or process optimization.

  • Contributions to open-source projects or publications in AI-related conferences/journals.

  • Familiarity with probabilistic programming languages (e.g., TensorFlow Probability, Pyro) and probabilistic reasoning methods (e.g. Bayesian NNs or Monte Carlo Tree Search).

  • Experience with industrial equipment and systems, particularly in manufacturing, semiconductors, or other high-precision environments.

  • Proven ability to contribute significantly to strategic initiatives and innovative projects.

  • A "defensive AI engineering" mindset, with experience handling the challenges of working with non-deterministic AI systems.

  • Proactive and adaptable mindset, thriving in a dynamic environment.

Equal Employment Opportunity Statement

Normal Computing is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, veteran status, or any other legally protected status.

Accessibility Accommodations

Normal Computing is committed to providing reasonable accommodations to individuals with disabilities. If you need assistance or an accommodation due to a disability, please let us know at accomodations@normalcomputing.ai.

Privacy Notice

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