Hop Labs Looking for ML Software Engineer at Atlanta, GA Full Time

Hop’s growing again! And as part of that, we’re hiring for an ML Software Engineer role. For more information about the company and the team, please check out our website.

About Hop

Before we get into what the role looks like, here are a few quick facts about Hop Labs:

• 100% remote, primarily based in the U.S.
• 10-15 team members, depending on our project mix at any given time
• Exclusively focused on technical consulting around production-scale machine learning
• Multiple Fortune 10 clients, several Fortune 100 clients, and a long tail of funded startup clients
• Results-oriented work environment with a lot of flexibility — we value life outside of work

Hop Labs is a boutique technical consulting firm solving applied machine learning problems in the real world. We’re client- and industry-agnostic, with a preference for projects that generate positive externalities. Because of our small size, we’re able to ensure that each project we take on is high-value — that project goals are achievable with present-day technology, that successful completion translates directly into business impact, and that there is close fit between our expertise and the needs of the project. Simply put: We apply machine learning to solve real-world problems, and we apply it well.

Requirements

We’re looking to hire an ML Software Engineer on an employee or independent contractor basis. Titles can be arbitrary, so you should consider yourself a good fit for this if:

• You have experience building and improving ML-powered systems and an interest in developing your skills there – bonus points if you’re interested in LLMs, generative AI, or deep learning in general.
• You enjoy solving hard technical problems at scale, for real business impact.
• You’re comfortable proposing end-to-end technical architectures that balance modularity, scalability, operations, security, and cost.
• You understand that clarity and simplicity — in code and in communication — are worth striving for.

As a distributed team, some key qualities are particularly important for all of us at Hop Labs:

• A strong sense of ownership and initiative: You take your task or issue seriously and proactively drive it start-to-finish.
• Clear and consistent communication: You can speak to lay people and engineers alike about issues, and keep teammates and clients informed on progress.
• A collaborative mindset: You approach your work as part of a larger team effort, and can take and give constructive feedback well.
• Clear thinking and attention to detail for complex projects: You are committed to a crisp understanding of what you’re doing and why, paired with careful planning and attention to details.
• Comfort with operating independently as well as part of a small, targeted team: You are flexible in working successfully in either context, in a fully remote environment.

For This Role Specifically

• Experience with construction and design of the entire ML pipeline, including training, deployment, and hosting in a production environment, using engineering best practices (e.g., unit testing, monitoring, logging)
• Fluency in the Python ML/data science stack (e.g., PyTorch, Scikit-Learn, Pandas)
• Proficiency in cloud engineering (AWS/Azure/GCP) and infrastructure-as-code (e.g., Terraform or equivalent)
• Proficiency with ETL/data pipelines and data stores
• Facility with web application technologies (e.g., Flask, UI development)
• Open to all backgrounds, though deep learning/LLM background strongly preferred
• Intermediate to senior level
• Location: remote within the U.S.

Residency and authorization to work in the U.S. is required.

If this role sounds like a good fit for you, please apply! We’ve made an effort to create a hiring process that is low-pressure, skills-focused, and compatible with the other commitments in your life.

Benefits

We offer a full slate of benefits at Hop for our employees:

• Medical, dental, and vision insurance with HSA option
• Mental health benefits
• Life and disability insurance
• Paid holidays and vacation time
• Flexible work schedules