Sr. Machine Learning Engineer

San Francisco, CA
Engineering /
Full-time /
Front is the modern customer service platform that helps companies delight their customers, engage their teams, and build stronger businesses. We’ve reimagined the help desk for real-time team collaboration across every customer communication channel, then powered it up with AI and automation to resolve issues and help teams work faster. Customers get exceptional service whether they’re looking for a simple, instant answer, or personalized help on their most complex issues — and you get the analytics and insights your business needs to optimize your customer experience. Over 8,500 businesses of all shapes and sizes, from ClickUp to Branch Insurance, Echo Global Logistics to Reed & Mackay rely on Front to deliver game-changing service that wins and retains customers for life.

Backed by Sequoia Capital and Salesforce Ventures, Front has raised $204M from leading venture capital firms and independent investors including top executives at Atlassian, Okta, Qualtrics, Zoom, and PagerDuty. Front has received numerous Great Place to Work accolades, including Y Combinator's list of Top Companies in 2023, #4 on Fortune’s Best Workplaces in the Bay Area™, Inc. Magazine's 2022 Best Workplaces list, Forbes Best Startup Employers 2022 List, and Best workplaces for Millennials 2022 list.

Front has been a steward of valuable communication data and patterns from thousands of its customers. This puts Front in the unique position of building highly relevant and personalized functionality that can drive large efficiency gains for its customers. We are seeking a Sr. Machine Learning Engineer with a bias for impact to join our dynamic engineering team. This role is crucial for leveraging the latest advancements in Machine Learning and AI to enhance our product offerings, particularly in natural language processing (NLP), content generation, and predictive analytics. You'll be pivotal in bringing Machine Learning solutions to life, from conception to deployment, and working alongside cross-functional teams to integrate these technologies seamlessly into our products.

To excel in this position, you must demonstrate strong learning abilities, showcase proven ML development skills, possess a mindset that aligns with being both a product and business-oriented engineer, have prior experience leading engineering teams, and work effectively within small, dynamic cross-functional settings.

What will you be doing?

    • Design and develop advanced Machine Learning (ML) models to solve challenging problems related to natural language processing (NLP), recommendation systems, and predictive analytics.
    • Collaborate with product and engineering teams to understand business needs and identify opportunities for the application of ML and AI technologies.
    • Lead the exploration of new ML techniques and technologies to enhance the capabilities of our products and improve the user experience.
    • Pioneer the exploration and adoption of new Generative AI techniques
    • Mentor junior engineers and ML specialists, fostering a culture of innovation and continuous learning within the team.
    • Ensure the quality and availability of data for model training and evaluation.
    • Continuously evaluate and improve the performance and scalability of ML models in production environments.
    • Stay abreast of developments in the field of ML and AI, and advocate for the adoption of industry best practices and emerging technologies.

What skills and experience do you need?

    • 5+ years of experience in designing, implementing, and deploying ML models, with a strong portfolio of projects that demonstrate your expertise.
    • Deep understanding of ML algorithms, data structures, and software engineering principles.
    • Proficiency in programming languages such as Python and experience with ML frameworks like TensorFlow, PyTorch.
    • Demonstrable experience driving impact by building production applications using ML models and learning based on production analytics and data.
    • Practical experience with natural language processing (NLP) technologies, recommendation systems, predictive analytics, Generative AI.
    • Strong experience with prompting techniques, RAG pipelines, evaluation mechanisms and fine-tuning SLMs, LLMs preferred.
    • Strong problem-solving skills and the ability to work independently as well as in a team environment.
    • Excellent communication skills, with the ability to convey complex technical concepts to non-technical stakeholders.


    • Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field.
    • Experience with cloud computing platforms like AWS, Google Cloud Platform, or Azure, especially with services related to ML and data analytics.
    • Familiarity with MLOps tools like Weights & Biases, MLFlow, Metaflow, Modal, etc.
    • Familiarity with containerization and orchestration technologies such as Docker and Kubernetes, particularly in the context of deploying and scaling ML models.
    • Advanced knowledge in specialized areas of ML such as deep learning, reinforcement learning, or unsupervised learning techniques.Contributions to open-source ML projects or active participation in ML communities and conferences.
    • Experience in developing and implementing ML solutions in the SaaS industry or for collaborative/team-based applications.
    • Practical experience with big data technologies such as Hadoop, Spark, or Kafka for processing and analyzing large datasets.
    • Proficiency in additional programming languages (e.g., JavaScript, R) or experience with front-end technologies (e.g., JavaScript, React, Angular) for end-to-end ML system development.
    • Published research papers in top ML or AI conferences and journals.
The San Francisco hiring salary range for this full-time position is $184,000 - $280,000 USD. Individual compensation packages are based on factors unique to each candidate, including job-related skills, experience, qualifications, work location, training, and market conditions. At Front, we take a market-based approach to pay. In addition to cash compensation (base salary, which may include commissions or overtime pay where applicable), Fronteers are eligible to receive equity in the company. This resource will provide additional information on our location zone designations. If you have questions, please speak with a member of our recruiting team for additional information.

These ranges may be modified by Front at our sole discretion in the future

What we offer
✨ Competitive salary
🤝 Equity (we are post-series D & backed by some of the best VCs in the US)
🏥 Private health insurance fully covered by Front
💪 Flexible Fridays - learn more here!
🏡 Flexibility to work from home 3 days/week (unless posted as a full-remote role)
🛋 Mental health support with Modern Health
🍼 Family planning support with Maven

Front provides equal employment opportunities (EEO) to all employees and applicants for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, age or disability. By applying, you acknowledge and agree that you have read and understand the California Recruiting Privacy Notice.