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Senior Machine Learning Engineer

Who is Aiwyn and what do we do?


Aiwyn is the fastest-growing software company serving the accounting profession. Founded in 2020, we now work with 100+ of the largest CPA firms in the world. Our “Job to be done”: speed up cash flow, save Partner time, & deliver best-in-class client experiences. We do this by automating day-to-day firm operations with our Practice Automation solutions. Aiwyn is led by serial entrepreneurs with multiple exits and funded by top-tier investors (Bessemer, KKR, & Revolution). We're passionate about building a remarkable company with world-class people, processes, and technology.


To learn more, visit our website


Job Summary:


We are seeking an experienced Senior Machine Learning Engineer to design, develop, and implement solutions across a wide range of business problems. The AI Engineering team is tasked with building AI into the fabric of both our products and our operations company-wide at Aiwyn. To deliver, not only must you have exceptional technical skills, you will also need to partner effectively with SMEs to deliver maintainable solutions and uplevel the understanding of and adoption of AI/ML everywhere we touch.


You will build pipelines that support the consumption and interpretation of complex document corpora, each with a variety of encoded knowledge. You will work extensively with knowledge graphs, modern AI/ML tools, and GAI infrastructure, while collaborating across frontend and backend teams (in a mostly Python stack) to ensure rapid iteration and deployment of AI solutions.


Key Responsibilities:
  • Solution Design, Development & Evaluation:
  • Collaborate with stakeholders to define business problems and determine the best AI/ML approaches.
  • Design and implement robust, scalable, and efficient machine learning systems to support the ingestion, processing, and interpretation of large document corpora.
  • Develop machine learning models, particularly in the context of knowledge graphs, to enhance the interpretation and utility of complex datasets.
  • Implement evaluation frameworks to assess model performance, iterating rapidly based on feedback and results.

Generative AI Expertise and Education: 
  • Leverage your deep knowledge of Generative AI (GAI) to stay ahead of industry trends and evaluate and integrate the latest advancements into our workflows. 
  • Integrate GAI into existing and new machine learning pipelines, enhancing the overall capability of our products.
  • Integrate observability and evaluation into our GAI applications to ensure consistent system performance.

Build an AI-centric Company:
  • Engage with stakeholders to help them understand what is possible and enable them to get their hands dirty prototyping and building their own AI-driven solutions.
  • Engage with the internal AI/ML community to share knowledge, stay informed of emerging trends, and integrate innovative ideas into our work.


Qualifications:
  • 5+ years of experience in machine learning engineering, with a focus on AI/ML solution development and delivery.
  • Proven expertise in working with Generative AI (GAI) and staying at the forefront of advancements in the field. 
  • Expert proficiency in Python, with experience in cross-language collaboration and codebase management. 
  • Proven experience collaborating across cross-functional teams to drive AI/ML adoption and impact. 
  • Advanced knowledge of AI/ML model development, evaluation, and rapid iteration. 
  • Strong problem-solving skills, with the ability to architect and implement scalable solutions for complex problems.
  • Experience with MLOps and delivering solutions in a cloud environment (e.g. GCP, AWS, Azure).
  • Strong experience with modern version control systems (e.g., GitHub). 
  • Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced, start-up environment.
  • The ability to travel occasionally for onsite Company meetings


Why Work at Aiwyn?
  • The big-picture value proposition of this role is simple: join us, and you'll be paid competitively to have freedom in solving worthwhile, challenging problems alongside other A-players at a fast-growing SaaS startup led by an experienced and successful team with industry experience.

Other benefits include:
  • Adventure travel stipend - you receive a $1,000 travel reimbursement on your work anniversary each year. We encourage our team to recharge and explore the world beyond their home office walls.
  • Remote, work-from-anywhere culture
  • Flexible PTO
  • World Class health benefits - we believe in fostering flourishing teams by providing benefits that go beyond the usual standards - Health, vision, dental, HSA/FSA, and mental health support.
  • Stock options - every Full Time Employee has ownership in Aiwyn's future and success.
  • 401(k) matching


Our Values:
  • Trust - We champion transparency, welcome differing perspectives, uphold accountability, and trust that others have good intentions
  • Courage - We have the courage to take calculated risks and embrace change, knowing what worked in the past won’t always work in the future
  • Impact - Rooted in determination and innovation, we chase extraordinary outcomes and impactful results
  • Relentlessness - We approach challenges with an unwavering resolve, never settling for mediocrity, and always striving to surpass expectations


Learn more about Aiwyn


Aiwyn is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances.


Candidate information will be treated in accordance with our CCPA privacy notice which can be found here: https://www.aiwyn.ai/ccpa

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What You Should Know About Senior Machine Learning Engineer, Aiwyn

As a Senior Machine Learning Engineer at Aiwyn, you will be joining an innovative and rapidly growing software company that is revolutionizing the accounting profession. Our mission is to expedite cash flow, save valuable partner time, and enhance the client experience through our advanced Practice Automation solutions. You will be a pivotal part of our AI Engineering team, tasked with integrating AI into our products and operations. In this role, your days will be filled with collaboration as you define business challenges with stakeholders, design scalable machine learning systems, and develop models that enhance the way complex datasets interact with knowledge graphs. Your expertise in Generative AI will shine as you keep us ahead of industry trends and weave the latest advancements into our workflows. Aiwyn thrives on a remote work culture, allowing you the flexibility to work from anywhere while engaging with your team through effective communication and collaboration. We value courageous individuals who are not afraid to tackle challenging, worthwhile problems. At Aiwyn, you'll be part of a company that values trust, impact, and relentless pursuit of excellence, while also enjoying perks like a $1,000 adventure travel stipend, flexible PTO, and equity in the company's success. Join us if you’re ready to take your career to the next level while making an indelible mark in the world of AI and machine learning!

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer Role at Aiwyn
What are the main responsibilities of a Senior Machine Learning Engineer at Aiwyn?

The Senior Machine Learning Engineer at Aiwyn is responsible for designing, developing, and implementing advanced AI/ML solutions. This includes collaborating with stakeholders to define business challenges, building scalable machine learning systems, and developing models that enhance the interpretation of complex datasets, particularly through knowledge graphs.

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What qualifications are required to apply for the Senior Machine Learning Engineer position at Aiwyn?

To apply for the Senior Machine Learning Engineer position at Aiwyn, candidates should have at least 5 years of experience in machine learning engineering, a strong proficiency in Python, and proven expertise in Generative AI. Collaborative skills and knowledge of MLOps in cloud environments are also essential.

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How does Aiwyn support professional growth for Senior Machine Learning Engineers?

Aiwyn fosters professional growth for Senior Machine Learning Engineers by encouraging innovation and exploration of emerging trends in AI/ML. The company promotes collaboration with stakeholders and provides opportunities to prototype and build AI-driven solutions, enhancing individual expertise and knowledge.

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What tools and technologies would a Senior Machine Learning Engineer use at Aiwyn?

A Senior Machine Learning Engineer at Aiwyn would work extensively with modern AI/ML tools, knowledge graphs, and GAI infrastructure. Skills in utilizing version control systems like GitHub and familiarity with cloud environments such as AWS, GCP, or Azure are also vital in this role.

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What makes Aiwyn a great place for Senior Machine Learning Engineers to work?

Aiwyn offers a dynamic, remote work culture that values trust, courage, and impact. Employees enjoy competitive salaries, unique benefits like travel stipends, stock options, and flexible time off, making it a perfect environment for talented Senior Machine Learning Engineers to thrive and make significant contributions.

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Common Interview Questions for Senior Machine Learning Engineer
Can you describe the process you follow to design a machine learning solution?

When designing a machine learning solution, it’s important first to understand the business problem. After defining the goals, I gather relevant data, preprocess it for model training, select appropriate algorithms based on the problem type, and then evaluate the model using performance metrics before deploying it.

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How do you ensure the scalability of your machine learning models?

I ensure scalability by implementing modular architecture, optimizing data pipelines, utilizing cloud services for computation, and continuously monitoring model performance as data and requirements evolve to facilitate smooth scaling in production.

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What experience do you have with Generative AI?

I have worked extensively with Generative AI techniques, applying them for tasks such as text generation and data augmentation. I stay updated on advancements in the field and prioritize their integration into pipelines for enhancing the overall capability of AI solutions.

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How do you handle collaborating with cross-functional teams?

Collaboration is fundamental. I approach it by establishing clear communication, setting shared goals, and actively engaging with team members to incorporate their insights throughout the project lifecycle, ensuring we deliver cohesive solutions that align across business units.

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Can you give an example of a challenging machine learning problem you've solved?

One of the most challenging problems I encountered involved optimizing a model for natural language processing in a noisy dataset. I successfully improved model performance through rigorous data cleaning, feature engineering, and iterative testing, ultimately enhancing accuracy by 30%.

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What is your approach to model evaluation and iteration?

I adopt a systematic approach to model evaluation, employing cross-validation techniques and performance metrics like precision, recall, and F1 score. Based on feedback and outcomes, I iterate on the model design, continuously refining it to achieve optimal performance.

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Which machine learning frameworks do you prefer and why?

I prefer TensorFlow and PyTorch for their versatility and community support. TensorFlow is great for production environments allowing scaled deployments, while PyTorch offers intuitive development and flexible experimentation, making it ideal for research purposes.

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How do you stay updated with the latest trends in machine learning?

I regularly read industry-related publications, attend webinars, and participate in online forums. Engaging with the AI/ML community through meetups and conferences also allows me to share ideas and stay informed about the latest trends and technologies.

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How would you approach integrating AI into existing company products?

Integrating AI into existing products starts with assessing current capabilities and identifying areas where AI can enhance functionality. Through collaboration with product teams and iterative development, we can prototype solutions that efficiently leverage AI for product improvement.

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What strategies do you use for effective problem-solving in machine learning projects?

Effective problem-solving requires a structured approach: defining the problem clearly, gathering appropriate data, employing analytical techniques to derive insights, and continuously iterating based on findings while being open to innovative solutions and collaborations.

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Full-time, remote
DATE POSTED
February 12, 2025

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