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Lead Machine Learning Engineer

***This role is fully remote within the U.S. (occasional travel to meet teams or partners) with a preference for East Coast. To reduce spam, we're not posting it as remote.***

About Us:

We are a forward-thinking mortgage technology company dedicated to evolving the mortgage industry. Our mission is to make homeownership more affordable. We accomplish our goals by focusing on outcomes, working with existing industry participants, and leveraging emerging technologies. Novaprime is backed by industry-leading institutions and investors and is partnered with some of the largest institutions in the mortgage industry.

Job Description:

We seek an exceptional and skilled Machine Learning Engineer to lead Novaprime's ML team. In this role, you will be pivotal in designing state-of-the-art ML products and developing core infrastructure that powers Novaprime's solutions. As part of this role, you will lead Novaprime’s ML team and collaborate with stakeholders and our product organization to manage the team’s roadmap and execution.

You will focus on evaluating ML models and architectures, fine-tuning, integrating fully managed services, and scaling systems to meet enterprise demands. You will collaborate with the larger engineering organization to deliver efficient solutions from data ingestion and pre-processing to training, evaluation, deployment, and improvements. You are responsible for the team’s delivery of efficient and reliable solutions, including models, implementation of best practices in MLOps, monitoring, automated pipelines, model reproducibility, and facilitating seamless model versioning and rollout.

You are experienced enough to guide our machine learning strategy and own the end-to-end ML lifecycle, from ideation to production deployment, including debugging, iterating, and releasing new models. At the same time, you are excited to be hands-on and build solutions that help Novaprime realize our mission of making homeownership more affordable.

Responsibilities:

  • Develop and implement a technical strategy aligned with our business goals.

  • Design and implement various ML algorithms, approaches, architectures, and models to achieve key business outcomes.

  • Drive implementation and delivery of ML systems, including custom domain-specific and fully managed ML solutions.

  • Drive development from concept to market by combining various technologies and collaborating with a cross-functional team.

  • Lead implementation of ML platform and infrastructure to ensure optimal and scalable performance.

  • Implement new technologies that yield competitive advantages.

  • Assist engineers in their work and decision-making processes.

  • Develop monitoring systems to ensure functionality and efficiency.

  • Build quality assurance and data protection processes.

  • Collaborate with product managers, designers, and other stakeholders to develop strategies and implement new products and features.

  • Stay current with the latest technologies to maintain competitiveness and technological leadership in the market.

  • Various engineering-related tasks which continue to progress the organization’s mission.

Requirements:

  • B.S. in Computer Science or equivalent experience.

  • 10+ years of industry experience.

  • Knowledge of large-scale distributed application architecture, design, implementation and performance tuning.

  • Experience with working with PyTorch, and the Python scientific stack (Numpy, Scikit-Learn, Pandas, etc).

  • Experience with evaluating and launching open-source ML models.

  • Experience with LLMs and automated prompt engineering.

  • Experience with working with k8s and related technologies.

  • Experience with one of the cloud platforms AWS/GCP/Azure.

  • Experience with CI/CD tools like GitHub Actions, etc.

  • Track record collaborating with product managers, designers, and engineers to deliver products and features to customers.

  • Great written and verbal communication skills, sufficient for success in a remote and largely asynchronous work environment.

  • Demonstrated capacity to clearly and concisely communicate about complex technical, architectural, and/or organizational problems and propose thorough iterative solutions.

  • Positive and solution-oriented mindset.

  • Exceptional working in a team environment as well as independently.

  • Various tasks and responsibilities to further the organization’s success.

Desired Experience:

  • 6+ years of experience with machine learning algorithms and tools, artificial intelligence, deep learning, or natural language processing.

  • Leading ML teams.

  • Running and scaling RAG in production environments.

  • Experience with parallel GPU utilization.

  • Experience with developing machine learning platforms, frameworks, and/or infrastructure for production-ready systems.

  • Experience with designing production-ready domain data models for performant and scalable systems.

Benefits:

  • Competitive salary, equity, and benefits.

  • Mostly remote work.

  • Opportunity to make a difference for millions and their ability to be homeowners.

We are an equal opportunity employer and value diversity at our company. We do not discriminate based on race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.

Average salary estimate

$175000 / YEARLY (est.)
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$200000K

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What You Should Know About Lead Machine Learning Engineer, Novaprime

As a Lead Machine Learning Engineer at Novaprime, you'll be at the forefront of revolutionizing the mortgage industry from the comfort of your home, although we do appreciate the East Coast vibes! Our aim is to make homeownership more affordable by harnessing innovative technologies and collaborating with industry players. This isn't just a job—it's a chance to lead our talented ML team, where you'll design groundbreaking machine learning products and engineer the infrastructure that propels our solutions. You’ll be in charge of fine-tuning models, integrating managed services, and ensuring that our systems can scale to meet the high demands of the enterprise. Your leadership will guide the ML strategy while you get your hands dirty, actively participating in the development process. You will oversee everything from data ingestion to deployment, ensuring that best practices in MLOps are seamlessly implemented. With over a decade of experience under your belt, you’ll mentor engineers and foster collaboration with product managers and designers, all while focusing on outcomes that matter. The role also requires you to stay ahead of technological trends, so being inquisitive and passionate is vital. Join us in shaping the future of homeownership in a role that's as rewarding as it is challenging!

Frequently Asked Questions (FAQs) for Lead Machine Learning Engineer Role at Novaprime
What are the responsibilities of a Lead Machine Learning Engineer at Novaprime?

As a Lead Machine Learning Engineer at Novaprime, your primary responsibilities include designing and implementing advanced machine learning algorithms and architectures that drive our business goals. You'll lead the ML team, manage the roadmap and execution of projects, ensure effective collaboration with stakeholders, and develop reliable ML solutions. You'll also focus on integrating new technologies, establishing best practices in MLOps, and ensuring effective system performance.

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What qualifications are necessary for a Lead Machine Learning Engineer at Novaprime?

To qualify for the Lead Machine Learning Engineer position at Novaprime, candidates should possess a B.S. in Computer Science or equivalent experience along with a minimum of 10 years in the industry. Essential skills include proficiency in distributed application architecture and significant experience with ML frameworks like PyTorch, the Python scientific stack, and cloud platforms such as AWS, GCP, or Azure. Strong communication skills are critical for success in our remote work environment.

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What experience is desired for a Lead Machine Learning Engineer at Novaprime?

Desired experience for a Lead Machine Learning Engineer at Novaprime includes over 6 years of hands-on experience with machine learning algorithms, tools, and leading teams. Familiarity with large language models, automated prompt engineering, and developing production-ready systems are significant assets. Additionally, a background in running scalable applications and parallel GPU utilization will help you thrive in this role.

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How does Novaprime support employee growth for Lead Machine Learning Engineers?

At Novaprime, growth is fostered through collaboration and embracing new technologies. As a Lead Machine Learning Engineer, you will not only lead projects but also mentor fellow engineers while staying up-to-date with market trends. We value a positive and solution-oriented mindset, encouraging you to propose innovative ideas and solutions that could enhance your professional development and the team's capabilities.

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What is the work environment like for a Lead Machine Learning Engineer at Novaprime?

The work environment for a Lead Machine Learning Engineer at Novaprime is predominantly remote but encourages collaboration within a supportive team. We understand the importance of communication in a largely asynchronous setting, so effective networking and collaboration with product managers, designers, and engineers will be crucial to your success. We promote a culture of diversity, inclusivity, and respect while ensuring everyone contributes meaningfully toward our mission.

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Common Interview Questions for Lead Machine Learning Engineer
Can you describe your experience with machine learning algorithms relevant to the Lead Machine Learning Engineer role?

In your response, highlight specific algorithms you've worked with, how you've implemented them in past projects, and the outcomes achieved. Be sure to connect your experience with the machine learning technologies mentioned in the job description, such as PyTorch and the Python scientific stack.

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How do you approach collaboration with product managers and other stakeholders?

Discuss your communication style, how you foster effective teamwork, and provide examples of successful collaborations. Mention any frameworks you follow to ensure alignment across teams and how you address differing priorities.

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Could you explain a time when you had to overcome a significant challenge in a machine learning project?

Use the STAR method (Situation, Task, Action, Result) to detail a specific example. Identify the challenge, how you addressed it, the techniques used, and the positive outcome of your efforts.

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What is your experience with MLOps and how do you ensure model reproducibility?

Provide details on your experience with MLOps practices, focusing on how you implement monitoring, automated pipelines, and version control for models. Discuss tools you use and the importance of reproducibility in your processes.

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How do you stay current with emerging technologies in machine learning?

Share the resources you utilize, such as online courses, industry blogs, or conferences. Explain how staying informed has benefited your work and the teams you're a part of.

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Describe a technical strategy you've developed in the past and how it aligned with business goals.

Provide an example where you successfully crafted a technical strategy, detailing both the technical aspects and business implications. Highlight your thought process and how it delivered measurable outcomes.

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How do you handle debugging and iterating on machine learning models?

Detail your debugging process, including tools and methodologies you apply. Emphasize your iterative approach to model improvement, citing real instances where you enhanced models through this process.

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Can you explain your experience with large-scale distributed application architectures?

Discuss specific architectures you have worked with, focusing on challenges, solutions, and performance tuning. Elaborate on how this experience prepares you for the responsibilities at Novaprime.

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How would you prioritize tasks within your team to meet tight deadlines?

Talk about your prioritization techniques, possibly mentioning agile methodologies or tools you use for task management. Support your strategy with examples of how you've successfully met deadlines under pressure.

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What role do you think a Lead Machine Learning Engineer plays in a remote setting?

Reflect on the unique challenges and opportunities in a remote work environment. Emphasize the importance of clear communication, independence, and team cohesion, citing experiences that showcase your adaptability.

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Full-time, remote
DATE POSTED
April 19, 2025

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