What is a Software Engineer at Deepgram?

As a Software Engineer at Deepgram, you are stepping into a role that sits at the intersection of high-performance computing, deep learning, and developer-centric API design. Deepgram is not just wrapping existing speech-to-text models; the company builds end-to-end deep learning models from scratch to deliver the fastest and most accurate transcription and understanding capabilities in the industry.

In this position, you are responsible for building the robust infrastructure and applications that allow developers to integrate voice AI into their products seamlessly. Your work directly impacts the speed, reliability, and scalability of the platform. Whether you are optimizing low-level code for GPU inference, designing intuitive APIs for external developers, or building internal tools to accelerate model training, your contributions are critical to the company's mission of making every voice heard and understood by machines.

You will join a team that values technical excellence and autonomy. The engineering culture is one of "proving yourself" through practical application rather than theoretical exercises. You will work on complex problems involving real-time data streaming, massive scale, and the unique challenges of serving AI models with low latency.

Getting Ready for Your Interviews

Preparation for Deepgram is distinct because the process leans heavily on practical engineering skills rather than abstract algorithmic puzzles. You should approach your preparation with a mindset of a "builder" rather than just a "solver."

Interviews here are designed to mimic the actual work environment. You will be evaluated on the following key criteria:

Practical Coding & Refactoring – Deepgram places significant weight on your ability to write clean, maintainable code and, crucially, your ability to extend and refactor that code. You won't just be writing a script and forgetting it; you will be asked to revisit your own work, explain your decisions, and add features on the fly.

Requirement Analysis & Clarity – A critical evaluation point is how you interpret open-ended requirements. Interviewers assess whether you can navigate ambiguity, ask the right clarifying questions, and deliver a solution that meets the underlying business need, not just the technical specification.

System Design & API Usability – Since Deepgram is an API-first company, you must demonstrate a strong grasp of RESTful principles, data structures, and system architecture. You will be evaluated on how you design interfaces that are intuitive for other developers to use.

Communication & Ownership – You will face questions that dig into your past experiences and current design choices. Interviewers look for candidates who can defend their technical choices professionally, accept feedback, and demonstrate ownership over their code.

Interview Process Overview

The interview process at Deepgram is structured to verify your technical capabilities through hands-on work. It typically begins with a recruiter screen to align on timelines and background, followed by a technical screen. Unlike many industry standard screens that focus on whiteboard coding, Deepgram’s initial technical screen often involves a discussion with a senior engineer or hiring manager about your past projects, technical depth, and fundamental data structures, without necessarily requiring live coding at that stage.

If you pass the screen, the core of the evaluation is a Take-Home Assignment. You will be asked to build a basic application or API based on a set of requirements. This is not a throwaway task; it forms the foundation of your final round. Candidates often report that the instructions can be open-ended, so paying attention to detail and making sensible architectural decisions is vital.

The final stage is a virtual onsite, which is usually a concise, intense session lasting around 2.5 hours. The centerpiece of this onsite is a "live extension" session where you walk through your take-home assignment with an engineer and implement new features or refactor code in real-time (often 90 minutes). This is followed by a behavioral and culture fit interview with a hiring manager. The process is transparent, but the bar for code quality and practical execution is high.

This timeline illustrates a process that is relatively streamlined but technically rigorous. The heaviest lift for you will be the Take-Home Assignment and the subsequent Onsite Extension of that assignment. Plan your schedule to allow dedicated time for the take-home, as the quality of that code will dictate the difficulty of your final interview.

Deep Dive into Evaluation Areas

Deepgram’s process is designed to filter for engineers who can build production-ready software. The following areas are the primary focus of your assessment.

The Take-Home Assignment

This is the most critical part of the process. You will be given a prompt to build a functional application or API.

• Why it matters: It demonstrates your ability to structure a project, manage dependencies, and write clean code without someone watching over your shoulder.
• Evaluation: Reviewers look for code organization, error handling, documentation, and adherence to requirements.
• Strong performance: Submitting code that runs out-of-the-box, has clear instructions, handles edge cases, and is structured in a way that makes adding new features easy.

Live Coding & Refactoring (Onsite)

During the onsite, you will revisit your take-home submission.

• Why it matters: This mimics the real job—taking existing code and modifying it. It tests your familiarity with your own code and your ability to code under pressure.
• Evaluation: Can you navigate your codebase quickly? Do you write tests for the new features? How do you handle refactoring requests?
• Be ready to go over:
  • Feature Extension – Adding a new endpoint or modifying data flow.
  • Refactoring – Changing the underlying data structure or logic to improve performance.
  • Debugging – Identifying why a specific input might break your current logic.

Technical Experience & Fundamentals

In the earlier screens and parts of the onsite, you will discuss your background.

• Why it matters: Deepgram needs to know you understand the "why" behind the technologies you use.
• Evaluation: Depth of knowledge in your chosen language (often Rust, Go, or Python) and understanding of general engineering concepts.
• Be ready to go over:
  • Data Structures – Hash maps, trees, and lists, and when to use them.
  • Concurrency – Handling multiple requests, threading, or async patterns.
  • Database Design – Schema design and trade-offs between SQL and NoSQL.

Product Sense & Implementation

You may speak with a Product Owner or Manager who will show you designs or features.

• Why it matters: Engineers at Deepgram work closely with product to define technical feasibility.
• Evaluation: Do you ask about edge cases? Do you spot potential technical bottlenecks in a proposed design?
• Example scenarios:
  • "Here is a design for a new dashboard feature. How would you architect the API to support this?"
  • "We want to add real-time transcription status. How do we implement that feedback loop to the user?"

Key Responsibilities

As a Software Engineer at Deepgram, your daily work revolves around building high-performance systems. You will be responsible for designing, developing, and deploying software that powers the company's speech AI platform. This often involves working with Rust (a core language at Deepgram), Python, or Go to build low-latency APIs and microservices.

You will collaborate closely with the Research and Product teams. While the Research team builds the core models, your job is to ensure those models can be served reliably to thousands of concurrent users. This involves optimizing inference pipelines, managing data ingestion, and ensuring high availability.

You will also drive architectural decisions. Deepgram is a rapidly scaling startup, which means you aren't just maintaining legacy code; you are often building new services from the ground up. You will own the full lifecycle of your features, from technical design documents to testing, deployment, and monitoring in production.

Role Requirements & Qualifications

To succeed in this role, you need a blend of strong systems programming skills and a product-oriented mindset.

• Must-have skills:

  • Strong Coding Proficiency: Expertise in a systems language is highly valued. Rust is the primary language for high-performance components, though experience in C++, Go, or Python is also relevant if you are willing to learn.
  • API Design: Deep experience building and documenting RESTful or gRPC APIs.
  • System Architecture: Understanding of distributed systems, load balancing, and database management.
  • Data Structures: Solid grasp of computer science fundamentals.

• Nice-to-have skills:

  • Audio/Speech Processing: Familiarity with concepts like sampling rates, codecs, or ASR pipelines.
  • GPU Programming: Experience with CUDA or optimizing code for hardware acceleration.
  • Cloud Infrastructure: Experience with AWS, GCP, Docker, and Kubernetes.

Common Interview Questions

The questions at Deepgram are practical and often derived directly from the work you do during the interview process. Do not expect a standard list of LeetCode hard problems; instead, expect questions that probe your engineering judgment.

Take-Home Review & Architecture

• "Walk me through the architecture of the app you built. Why did you choose this specific folder structure?"
• "If we had to scale this application to handle 10,000 concurrent requests, what would break first?"
• "Why did you choose this specific database/storage solution for this assignment?"
• "How would you refactor this specific function to make it more testable?"

Technical Fundamentals

• "Explain how a Hash Map works under the hood. How are collisions handled?"
• "Describe a challenging technical bug you faced in a previous role. How did you debug it?"
• "What are the trade-offs between TCP and UDP, and which would you use for real-time audio streaming?"
• "How do you handle database migrations in a production environment without downtime?"

Behavioral & Product

• "Tell me about a time you disagreed with a product requirement. How did you handle it?"
• "How do you prioritize technical debt against new feature development?"
• "Describe a situation where you had to learn a new technology quickly to deliver a project."

Frequently Asked Questions

Q: Is the interview process heavy on LeetCode/Algorithms? The process focuses less on abstract algorithmic puzzles and more on practical application. While you should know your data structures (arrays, maps, trees), the primary assessment is your ability to build a working application and modify it.

Q: How much time should I spend on the Take-Home Assignment? Quality is more important than speed, but usually, these assignments are designed to take a few hours. However, candidates who treat it as a production-quality submission (clean code, comments, README, tests) tend to perform better in the next round.

Q: What is the "Live Extension" interview like? It is a collaborative coding session. You will share your screen, and the interviewer will act as a peer. They might say, "Let's add a feature that filters these results." You are expected to implement it in your existing codebase while talking through your thought process.

Q: Does Deepgram offer remote roles? Yes, Deepgram is generally remote-friendly for engineering roles, though they may have hubs or periodic meetups. Be sure to clarify specific team expectations with your recruiter.

Q: What if I don't know Rust? While Rust is heavily used at Deepgram, strong engineers with backgrounds in C++, Go, or other systems languages are often considered if they demonstrate the aptitude to learn quickly.

Other General Tips

• Treat the Take-Home like Production Code: Do not cut corners on the take-home assignment. Add a README.md that explains how to run it, your design decisions, and what you would improve with more time. This is often the single biggest differentiator.
• Clarify "Open-Ended" Requirements: If a requirement seems vague, it might be a test of your product sense. State your assumptions clearly in your documentation or ask the recruiter for clarification before starting.
• Prepare for "Free Consulting" Scenarios: Some candidates feel that product interviews can get very specific about real features Deepgram is building. Approach these as collaborative brainstorming sessions where you can showcase your expertise, but stay focused on the principles of the solution.
• Know Your Resume: You will be asked specific questions about the technologies and projects listed on your resume. If you list a skill, be ready to answer deep technical questions about it.
• Culture of Autonomy: Deepgram values engineers who can run with a problem. During behavioral questions, highlight examples where you took ownership of a vague problem and drove it to a solution.

Summary & Next Steps

Deepgram offers a unique opportunity for Software Engineers to work on cutting-edge voice AI technology. The role requires a "builder" mindset, where practical coding skills, system design, and the ability to navigate ambiguity are paramount. You will be challenged to prove your skills through hands-on coding and architectural discussions rather than abstract theory.

To succeed, focus your preparation on practical software engineering: writing clean APIs, understanding your own code deeply, and being able to refactor on the fly. Review your fundamentals, but prioritize your ability to deliver working, scalable software. A successful interview here is not just about getting the right answer; it's about demonstrating that you are a thoughtful, collaborative engineer who is ready to contribute to a high-performance team.

The compensation data above reflects the competitive nature of the role. Deepgram typically offers a mix of base salary and equity, which is standard for high-growth AI startups. Ensure you understand the full package, including the potential value of the equity component, as this is a significant part of the long-term reward.

For more insights into interview questions and community discussions, you can explore further on Dataford. Good luck—prepare well, build carefully, and show them what you can create.