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Senior Machine Learning Engineer - US Remote

About Influur

Influur is the first startup that works as an app-based marketplace by directly creating jobs for Influencers, Creators, and Brands around the world. The company was born from the communication struggles between influencers and brands, an experience that like many others, our founding team had at some point in their careers. We have created a streamlined solution built from the influencer perspective, making  Influur the first platform where influencers feel they belong in a professional space.


At Influur, our leadership team loves working side by side with our team, providing unique opportunities to grow and develop, professionally and personally. Also, since day one, we have been truly people oriented as we understand the value of co-creating while offering a unique employee experience.


The Role

We are seeking a highly skilled and motivated Machine Learning Engineer to join our team. As our first dedicated MLE, this role requires a self-driven individual with exceptional leadership and communication abilities. You will be responsible for designing, implementing, and deploying ML models that directly impact our product and customers, collaborating closely with cross-functional teams to drive data-driven decision-making and innovation.


Key Responsibilities
  • Design, develop, and deploy machine learning models to improve influencer-brand matching, content recommendations, and other core platform features.
  • Build scalable and production-ready ML pipelines that support real-time and batch processing.
  • Ensure model accuracy, performance, and robustness through rigorous testing and evaluation.
  • Work closely with product managers, engineers, and data scientists to define ML objectives and integrate models into our platform.
  • Lead ML initiatives and evangelize best practices across the organization.
  • Support in the recruiting process of future ML hires.
  • Provide mentorship and guidance to future ML hires.
  • Partner with data engineers to ensure the availability of high-quality training data.
  • Analyze large-scale influencer marketing data to uncover insights and inform ML strategies.
  • Develop and maintain feature engineering pipelines to enhance model performance.
  • Leverage cloud platforms (AWS, GCP) to deploy and scale ML solutions.
  • Optimize ML workflows for efficiency and cost-effectiveness.
  • Establish monitoring and continuous improvement frameworks for deployed models.


Desired Background
  • 6+ years of experience in machine learning engineering, with a track record of deploying ML models in production environments.
  • Strong proficiency in Python and ML frameworks such as TensorFlow, PyTorch, or Scikit-learn.
  • Experience with data processing frameworks such as Spark or distributed computing.
  • Knowledge of MLOps best practices, including CI/CD for ML models.
  • Strong understanding of deep learning, NLP, recommendation systems, and computer vision.
  • Excellent problem-solving skills and ability to work independently in an ambiguous environment.
  • Exceptional communication skills and the ability to collaborate effectively with cross-functional teams.


Bonus Skills
  • Experience in influencer marketing, social media analytics, or similar domains.
  • Familiarity with cloud platforms like AWS or GCP.
  • Understanding of data engineering tools such as Airflow, dbt, or BigQuery.
  • Experience in working with graph-based or recommendation systems.


$150,000 - $200,000 a year
Gross salary

What makes us unique

• At Influur, we’re committed to your growth and development every step of the way 🚀

• You’ll thrive in a diverse, fast-paced startup environment ⚡

• You’ll collaborate with a world-class team that pushes boundaries and inspires greatness 👩‍🚀👨‍🚀

• Our one-of-a-kind culture will bring out the very best in you! 🧡

• Plus, you’ll have access to real stock options—because we believe in sharing success! 💹

Average salary estimate

$175000 / YEARLY (est.)
min
max
$150000K
$200000K

If an employer mentions a salary or salary range on their job, we display it as an "Employer Estimate". If a job has no salary data, Rise displays an estimate if available.

What You Should Know About Senior Machine Learning Engineer - US Remote, Influur

At Influur, we're on the lookout for a dynamic Senior Machine Learning Engineer to join our innovative remote team in the USA. As pioneers in the creator economy, Influur bridges the gap between influencers and brands through a unique app-based marketplace. This role is perfect for a self-driven individual with strong leadership and communication skills who wants to design, implement, and deploy cutting-edge machine learning models that enhance the way influencers and brands connect. You'll leverage your expertise to improve our algorithm-driven features, ensuring accurate and robust model performance. Collaborating with a passionate team across various functions, you'll play a key role in driving data-driven strategies that elevate our platform's offerings. Your responsibilities will include building scalable ML pipelines, conducting rigorous model evaluations, and providing mentorship to future ML hires. With a focus on continuous improvement and innovation, you'll work with state-of-the-art technology in a vibrant startup atmosphere. If you have a passion for machine learning and want to contribute significantly to a growing company that values your input, Influur could be your next exciting opportunity!

Frequently Asked Questions (FAQs) for Senior Machine Learning Engineer - US Remote Role at Influur
What are the key responsibilities of a Senior Machine Learning Engineer at Influur?

As a Senior Machine Learning Engineer at Influur, your primary responsibilities include designing, developing, and deploying ML models that enhance influencer-brand matching and content recommendations. You will also be tasked with building scalable ML pipelines that support real-time and batch processing, ensuring model accuracy and performance, and collaborating closely with cross-functional teams. Additionally, you will lead ML initiatives, mentor future hires, and develop feature engineering pipelines.

Join Rise to see the full answer
What qualifications are required for the Senior Machine Learning Engineer position at Influur?

To excel as a Senior Machine Learning Engineer at Influur, you should have at least 6 years of experience in machine learning engineering, with a proven track record of deploying models in production. Strong proficiency in Python and ML frameworks like TensorFlow or PyTorch is essential. Moreover, you should possess knowledge of MLOps best practices, deep learning, and recommendation systems, alongside excellent problem-solving and communication skills.

Join Rise to see the full answer
What benefits and growth opportunities can I expect as a Senior Machine Learning Engineer at Influur?

Joining Influur as a Senior Machine Learning Engineer means you'll enjoy unique opportunities for professional growth and development. The company culture promotes diversity and collaboration, offering an environment where you can thrive. Additionally, you'll have access to real stock options, reflecting our commitment to sharing success with our team members.

Join Rise to see the full answer
How does Influur support machine learning initiatives?

At Influur, we support machine learning initiatives by encouraging collaboration across teams and fostering a culture of innovation. As a Senior Machine Learning Engineer, you will lead ML initiatives and help integrate models into our platform, working closely with product managers and data engineers to ensure that ML objectives are aligned with business goals and that high-quality training data is available.

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What is the salary range for the Senior Machine Learning Engineer position at Influur?

The gross salary for the Senior Machine Learning Engineer position at Influur ranges from $150,000 to $200,000 annually. This competitive compensation reflects the value we place on your skills and expertise in contributing to our innovative marketplace.

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Common Interview Questions for Senior Machine Learning Engineer - US Remote
Can you describe your experience with deploying machine learning models in production?

During your response, highlight specific projects where you successfully deployed ML models, discussing the challenges you faced and the solutions you implemented. Showcase your understanding of MLOps and relevant tools such as CI/CD pipelines.

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What frameworks and tools do you prefer for machine learning in your projects?

Discuss your preferred ML frameworks, such as TensorFlow or PyTorch, and explain why you favor them. Include examples of how you’ve utilized these tools to achieve project goals effectively.

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How do you ensure the accuracy and reliability of machine learning models?

Outline your approach to model validation, including techniques like cross-validation and establishing performance metrics. Emphasize the importance of continuous testing and improvement.

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Describe a machine learning challenge you faced and how you overcame it.

Select an example that demonstrates your problem-solving skills. Discuss the context, the steps you took to address the challenge, and the positive outcomes of your efforts.

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What role does feature engineering play in your machine learning process?

Explain your understanding of feature engineering and its significance. Provide examples of features you've engineered in the past and how they impacted model performance.

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

Share your strategies for continuous learning, such as following influential researchers, attending conferences, or participating in online courses and communities, highlighting your commitment to staying at the forefront of the field.

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Can you describe your experience working with large datasets?

Discuss your familiarity with big data technologies and frameworks like Apache Spark. Provide examples of how you processed and analyzed large datasets in past roles.

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How do you approach collaborating with cross-functional teams?

Talk about your communication skills and how you’ve worked with product managers, engineers, and designers. Emphasize your ability to translate technical concepts into layman’s terms to foster understanding.

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What metrics do you consider when assessing model performance?

Mention key performance indicators (KPIs) like accuracy, precision, recall, and F1-score. Discuss how choosing appropriate metrics is critical to aligning with business objectives.

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Have you ever mentored junior machine learning engineers? What was your approach?

Share your mentoring experiences, discussing how you supported junior engineers in their professional development. Highlight techniques you used to provide constructive feedback and encourage knowledge sharing.

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We are revolutionizing how online advertising is been done.

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Full-time, remote
DATE POSTED
March 17, 2025

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