How to Apply to Deepgram

Key Takeaways

Before applying, sign up for a free Deepgram API account and build something — even a simple transcription demo shows you've moved beyond casual interest into hands-on engagement with the product.
Customize your resume for the specific Deepgram role using exact terminology from the job description, their documentation, and their blog — Ashby's search makes keyword alignment directly impact your visibility to recruiters.
Research Deepgram's competitive landscape (AssemblyAI, OpenAI Whisper, Google Cloud Speech-to-Text, Amazon Transcribe) and prepare a point of view on Deepgram's differentiation — this question comes up in nearly every interview round.
Format your resume as a clean, single-column PDF with standard section headers to ensure Ashby's parser creates an accurate candidate profile — formatting errors can sink an otherwise strong application.
Prepare concrete stories demonstrating ownership, speed, and cross-functional collaboration — Deepgram is a startup where everyone operates beyond their job description, and your examples should reflect that reality.
Follow Deepgram's engineering blog, research publications, and social media channels to stay current on their latest model releases and product updates — referencing recent announcements in interviews signals you're tracking the company closely, not just applying broadly.

About Deepgram

Deepgram is a speech AI company building the foundational infrastructure for how machines understand and generate human voice. Their core products — automatic speech recognition (ASR), text-to-speech (TTS), and voice AI agent APIs — are built on proprietary deep learning models trained from scratch, setting them apart from competitors who rely on older, rules-based approaches or fine-tuned open-source models. This end-to-end AI-native architecture gives Deepgram a significant speed and accuracy advantage, processing speech in real-time with enterprise-grade reliability. Positioned at the intersection of AI infrastructure and developer tools, Deepgram serves thousands of companies — from startups building voice assistants to enterprises processing millions of audio hours. Their API-first approach has earned them a devoted developer community, and their technology powers use cases spanning contact center analytics, real-time transcription, conversational AI agents, and media intelligence. Culturally, Deepgram operates with the intensity and velocity of a well-funded AI startup. Founded by a team with deep roots in applied physics and machine learning research, the company prizes intellectual rigor, builder mentality, and a bias toward shipping. Their distributed workforce spans multiple continents, as evidenced by active roles in EMEA and APAC regions, reflecting a genuinely global operation rather than a headquarters-centric company with satellite offices. The research team publishes and contributes to the broader AI community, and engineers regularly interact directly with customers — blurring the lines between R&D and go-to-market in ways that attract people who want their work to have immediate, visible impact. For candidates passionate about voice AI during a period of explosive growth in the space, Deepgram represents a rare opportunity to work on foundational technology rather than incremental product features.

Application Process

Explore Open Roles on Deepgram's Careers Page
Visit deepgram.com/company/careers to browse their approximately 41 active positions spanning research, engineering, go-to-market, and customer success. Roles are distributed globally, so filter carefully by function and region — a 'Customer Success Engineer (APAC)' and an 'EMEA Account Executive' signal that location and timezone alignment matter significantly for certain positions. Read each job description thoroughly, as Deepgram tends to be specific about the technical domain (e.g., 'Research Staff, Voice AI Foundations' vs. 'Research Staff, LLMs'), and applying to the wrong sub-specialty wastes both your time and theirs.
Submit Your Application Through Ashby
Deepgram uses Ashby as their applicant tracking system, which means your application flows through a modern, structured pipeline. Expect a clean application form that typically asks for your resume, LinkedIn profile, and possibly a few short-answer or role-specific questions. Complete every field — Ashby's parsing is solid, but incomplete applications can be filtered out before a human ever sees them.
Recruiter Screen (30-45 Minutes)
If your application advances, a recruiter or talent team member will typically schedule an initial phone or video screen. For a company like Deepgram, expect this conversation to probe your understanding of the voice AI / speech technology space, your motivation for joining a startup at this stage, and basic alignment on role expectations, compensation range, and logistics like timezone or travel requirements. Demonstrate that you've actually used the Deepgram API or at least explored their documentation — this signals genuine interest rather than a spray-and-pray application.
Hiring Manager Deep-Dive
The hiring manager interview typically goes deeper into your domain expertise and how you'd contribute from day one. For research roles, expect detailed discussion of your publication history, model architecture choices, and experience with speech or language model training at scale. For GTM roles like Strategic Account Executive, prepare to discuss deal cycles, enterprise sales motion in developer-tools or API-first companies, and how you'd position Deepgram against competitors like AssemblyAI, OpenAI Whisper, or Google Cloud Speech-to-Text. This round is where Deepgram assesses whether you can operate at startup speed with enterprise-level rigor.
Technical or Functional Assessment
Depending on the role, this stage varies considerably. Engineering and research candidates commonly face a take-home project or live coding session focused on real problems Deepgram encounters — think audio processing pipelines, model optimization, or infrastructure scaling challenges. GTM candidates may be asked to deliver a mock product demo, build a prospecting plan, or walk through a deal strategy. Customer Success Engineers should prepare for scenario-based exercises involving API troubleshooting and customer communication. The assessment is designed to simulate actual work, not abstract puzzle-solving.
Cross-Functional and Culture Fit Interviews
Deepgram's collaborative culture means you'll likely meet team members from adjacent functions. An engineer might speak with a product manager and a researcher; a sales hire might meet someone from customer success and marketing. These conversations assess whether you can communicate across disciplines — a critical skill at a startup where roles overlap frequently. Demonstrate curiosity about how other teams work, ask thoughtful questions about collaboration norms, and show you understand that at a company Deepgram's size, everyone wears multiple hats.
Final Decision and Offer
Deepgram's hiring process, like most well-run startups, tends to move faster than enterprise companies — many candidates report timelines of two to four weeks from application to offer. The offer stage typically involves a conversation about total compensation, which at a venture-backed startup often includes equity alongside base salary. Be prepared to discuss your expectations openly, and don't hesitate to ask about vesting schedules, the company's latest funding stage, and growth trajectory. If you receive an offer, the recruiter is usually your point of contact for negotiation.

Resume Tips for Deepgram

Critical Lead with Speech AI, NLP, or Voice Technology Experience

Deepgram's entire business is built on deep learning models for speech. If you have any experience with automatic speech recognition (ASR), text-to-speech (TTS), natural language processing, audio signal processing, or conversational AI, make it the most prominent content on your resume. Even tangential experience — like working with audio data pipelines, implementing real-time streaming architectures, or fine-tuning transformer models — should be elevated above more generic software engineering work. Recruiters scanning your Ashby profile will be pattern-matching for these specific domain signals.

Critical Mirror Deepgram's Technical Vocabulary Precisely

Study Deepgram's product documentation, blog posts, and job descriptions to identify the exact terminology they use — terms like 'end-to-end deep learning,' 'real-time transcription,' 'streaming API,' 'voice agents,' 'model inference,' and 'on-prem deployment.' Ashby's search and filtering capabilities allow recruiters to surface candidates by keyword, so using Deepgram's own language increases your visibility. Avoid outdated terms like 'speech-to-text engine' when Deepgram consistently uses 'automatic speech recognition' or 'ASR.'

Critical Quantify Impact with Metrics Relevant to AI Infrastructure

Generic metrics like 'improved efficiency by 20%' are less compelling than metrics that resonate with Deepgram's specific challenges. Think in terms of latency reduction (e.g., 'reduced inference latency from 200ms to 45ms'), throughput scaling ('architected pipeline handling 10,000 concurrent audio streams'), model accuracy ('improved word error rate from 12% to 7.3% on domain-specific data'), or developer adoption ('grew API integration adoption 3x in six months'). These numbers speak directly to the problems Deepgram solves daily.

Showcase Startup and High-Growth Experience

Deepgram is a venture-backed startup in a hyper-competitive AI market, not a Fortune 500 company. Highlight experiences where you operated with ambiguity, wore multiple hats, shipped under tight deadlines, or scaled something from zero to one. If you've worked at other AI startups, developer-tools companies, or API-first platforms (think Twilio, Stripe, or Hugging Face), make those connections explicit. A resume formatted entirely around large-enterprise experience without any startup context may signal a culture mismatch.

Include Open-Source Contributions and Published Research

Deepgram actively hires research staff and contributes to the AI community. If you've published papers (especially in speech, audio, or language modeling), contributed to relevant open-source projects, or have a strong GitHub profile demonstrating ML/AI work, include these prominently. For research roles, list key publications with venues (NeurIPS, ICASSP, Interspeech, ACL) and briefly note their impact. For engineering roles, link to repositories that demonstrate systems thinking, not just algorithm implementation.

Use Clean, ATS-Optimized Formatting for Ashby

Ashby parses resumes effectively, but overly designed templates with columns, text boxes, graphics, or unusual fonts can cause parsing errors that strip important context. Use a single-column layout with clear section headers (Experience, Education, Skills, Publications), standard bullet points, and a PDF or .docx format. Ensure your contact information, job titles, company names, and dates are in a consistent, predictable structure so Ashby can auto-populate your candidate profile accurately.

Tailor Your Skills Section to the Specific Role's Tech Stack

Deepgram's engineering roles span distinct domains — a Platform Engineer working on AI/ML Infrastructure needs different keywords than a Backend Software Engineer on the Active Learning Team. Review each job listing for specific technologies mentioned (e.g., Kubernetes, PyTorch, Rust, Go, Python, gRPC, Kafka) and ensure your skills section reflects genuine proficiency in those tools. A generic 'Python, Java, C++' list doesn't differentiate you; 'PyTorch, ONNX Runtime, Triton Inference Server, Kubernetes, Terraform' tells a much more specific story about your infrastructure-for-AI expertise.

Highlight Customer-Facing Technical Skills for Hybrid Roles

Roles like Customer Success Engineer and GTM Enablement Manager at Deepgram sit at the intersection of deep technical knowledge and client engagement. If you're applying for these positions, your resume should demonstrate both — showcase API troubleshooting, technical documentation writing, developer community engagement, or solution architecture alongside communication skills and account management experience. Deepgram's product is inherently technical, and these roles require someone who can debug a WebSocket connection and explain the solution to a non-technical stakeholder in the same afternoon.

ATS System: Ashby

Ashby is a modern, analytics-forward ATS designed for high-growth companies that want structured, data-driven hiring. It combines applicant tracking, scheduling, CRM, and hiring analytics in one platform, and is favored by startups that take recruiting operations seriously. Deepgram's use of Ashby signals a thoughtful, process-oriented approach to talent acquisition — your application will be tracked, scored, and surfaced through structured workflows rather than sitting in an unmonitored inbox.

Submit your resume as a single-column PDF or .docx to ensure Ashby's parser correctly extracts your work history, skills, and education without formatting artifacts.
Complete every field in the application form — Ashby allows recruiters to filter candidates by completeness, and missing fields can deprioritize your application automatically.
Use exact keywords from the job description in your resume and any short-answer fields. Ashby's search functionality lets recruiters surface candidates by specific terms like 'ASR,' 'real-time streaming,' or 'voice AI.'
Avoid headers/footers, tables, multi-column layouts, and embedded images — these elements commonly cause parsing failures in Ashby and can result in blank or garbled candidate profiles.
If the application includes optional questions or a space for a cover note, always fill them in. Ashby tracks engagement signals, and fully completed applications demonstrate genuine interest in the role.
Keep your file name professional and descriptive (e.g., 'FirstName_LastName_Resume_Deepgram.pdf') — recruiters in Ashby can see file names when downloading resumes in bulk.

Complete Ashby Resume Guide

Interview Culture

Deepgram's interview culture reflects its identity as a research-driven AI startup: expect rigor without pretension, technical depth without gatekeeping, and a genuine interest in how you think — not just what you've memorized. Most candidates report a process spanning three to five rounds, typically completed within two to four weeks. The cadence is fast; Deepgram operates in one of the most competitive hiring markets in tech (AI/ML talent), and they know that dragging out a process loses top candidates. Expect responsive communication and reasonable scheduling flexibility, particularly given their distributed, global workforce. For research and engineering roles, technical interviews are the core of the process. Rather than LeetCode-style algorithm puzzles, Deepgram tends toward problems rooted in their actual domain — audio processing, model architecture decisions, inference optimization, and systems design for real-time data. You might be asked to walk through a research paper you've published, discuss trade-offs in a model architecture, or design a system that handles concurrent audio streams at scale. Come prepared to discuss your work at a deep technical level, but also to explain complex concepts clearly — cross-functional communication is valued even in deeply technical roles. For go-to-market positions (sales, customer success, marketing), interviews often include practical simulations. A Strategic Account Executive candidate might be asked to roleplay a discovery call or present a competitive positioning strategy. A Customer Success Engineer might troubleshoot a simulated API integration issue. These exercises test your ability to engage with Deepgram's developer-centric customer base authentically. Culture fit conversations typically explore your comfort with ambiguity, ownership mentality, and intellectual curiosity. Deepgram looks for people who are energized (not paralyzed) by rapid change, who default to action over process, and who are genuinely fascinated by the intersection of AI and human communication. Show that you follow the voice AI space closely, have opinions about where it's heading, and are excited about building during this particular moment in AI history. Arrogance is a red flag; confident humility — knowing what you know and being honest about what you don't — resonates strongly with Deepgram's research-rooted culture.

What Deepgram Looks For

Deep domain expertise in speech AI, NLP, or adjacent ML fields — Deepgram builds foundational models, not wrappers, and they need people who understand the science underneath
Builder mentality and ownership instinct — at a startup this size, they hire people who see a problem and fix it without waiting for a ticket to be assigned
Comfort with ambiguity and rapid iteration — Deepgram's market is evolving weekly, and they need people who can adapt their approach as the competitive landscape shifts
Strong communication across technical and non-technical audiences — even research staff are expected to articulate the business impact of their work
Genuine passion for voice AI and the future of human-computer interaction — candidates who can speak intelligently about the space, competitors, and emerging use cases stand out immediately
Global collaboration skills — with team members across multiple time zones and regions, asynchronous communication, cultural sensitivity, and documentation discipline are essential
API-first and developer-community awareness — whether you're in engineering, sales, or customer success, understanding how developers evaluate and adopt tools like Deepgram's API is a baseline expectation

Frequently Asked Questions

How long does the Deepgram hiring process typically take from application to offer?

Based on patterns common at AI startups of Deepgram's size and stage, most candidates report a timeline of two to four weeks from initial application to final offer. The recruiter screen is usually scheduled within one to two weeks of application if you're selected, and subsequent rounds tend to be scheduled in quick succession. Deepgram competes fiercely for AI talent and likely understands that slow processes lose top candidates. That said, research roles involving publication review or complex technical assessments may take slightly longer.

Should I include a cover letter when applying to Deepgram?

While Ashby may not always require a cover letter, including a brief, targeted one can differentiate you — especially for non-engineering roles where communication skills are a core competency. Keep it to 200-300 words maximum. Focus on why Deepgram specifically (not just 'AI is exciting'), what you'd contribute in the first 90 days, and one concrete example of relevant experience. For research roles, your publication list and a well-crafted resume may speak louder than a cover letter. For GTM roles like Strategic Account Executive or GTM Enablement Manager, a compelling cover letter demonstrates the persuasive writing skills you'll use daily.

What level of experience does Deepgram look for? Can I apply as an early-career candidate?

Deepgram's open roles span a range from mid-level to senior and staff positions, particularly in research (e.g., 'Research Staff, LLMs'). The 'staff' designation in their research titles typically implies significant experience — published research, advanced degrees, and meaningful contributions to the field. Engineering and platform roles may have broader experience ranges. For early-career candidates, the best approach is to demonstrate exceptional depth in a narrow, relevant area — perhaps a thesis on speech recognition, contributions to an open-source ASR project, or a portfolio of voice AI experiments. Startups like Deepgram occasionally hire high-potential junior candidates who show outsized initiative and domain passion.

Does Deepgram offer remote work opportunities?

Deepgram's active job postings across EMEA and APAC regions (including 'EMEA Account Executive' and 'Customer Success Engineer, APAC') strongly indicate a distributed, remote-friendly workforce. Many AI startups of Deepgram's profile operate in a remote-first or hybrid model, and their global hiring pattern suggests they prioritize talent access over geographic colocation. That said, specific roles may require timezone alignment for customer-facing responsibilities or team collaboration. Check individual job descriptions for location requirements, and ask your recruiter about expectations for overlap hours during the initial screen.

How should I prepare for a technical interview at Deepgram?

Focus preparation on Deepgram's actual domain rather than generic algorithm practice. For ML/research roles, review fundamentals of speech recognition architectures (CTC, attention-based encoder-decoders, conformer models), real-time inference optimization, and large language model training and fine-tuning. For infrastructure and backend roles, study distributed systems design for real-time audio streaming, low-latency API architecture, and ML model serving at scale. Explore Deepgram's API documentation, experiment with their product, and read their engineering blog to understand the specific technical challenges they face. Be prepared to discuss trade-offs, not just solutions — Deepgram values systems-level thinking over rote implementation skill.

What makes a strong application for Deepgram's go-to-market (sales, marketing, CS) roles?

Deepgram sells a deeply technical API product to developers and engineering teams, which means their GTM hires need genuine technical fluency — not just sales methodology. A strong application for roles like Strategic Account Executive or Customer Success Engineer demonstrates experience selling or supporting developer tools, API platforms, or AI/ML products. Highlight specific metrics: deal sizes in enterprise SaaS, developer adoption growth you influenced, or technical accounts you managed. Show that you understand PLG (product-led growth) and enterprise sales aren't mutually exclusive — Deepgram likely operates a hybrid motion where self-serve developers become enterprise accounts, and your experience navigating that transition is highly relevant.

How does Deepgram's Ashby ATS handle my application, and what should I optimize?

Ashby processes your application through structured pipelines where recruiters can filter, search, and score candidates based on profile completeness, keyword relevance, and stage progression. Your resume is parsed automatically to populate your candidate profile, so formatting matters — a clean, single-column layout with standard headings ensures accurate parsing. Recruiters can search across all applicants using specific terms, so embedding relevant keywords naturally throughout your resume (not just in a skills section) increases your chances of surfacing in searches. Complete every optional field in the application form, as thoroughness is both a signal of interest and a practical filter in Ashby's workflows.

What should I know about Deepgram's competitors before interviewing?

Deepgram operates in a competitive speech AI market alongside players like AssemblyAI (a close competitor in developer-focused ASR APIs), OpenAI's Whisper (open-source model that's widely adopted), Google Cloud Speech-to-Text, Amazon Transcribe, and Microsoft Azure Speech Services. Deepgram differentiates through its end-to-end deep learning approach, real-time processing speed, customization capabilities, and developer experience. Before your interview, form a genuine point of view on where Deepgram's advantages lie and where the market is heading — voice AI agents, real-time multimodal interaction, and on-device inference are active frontier areas. Demonstrating competitive awareness shows strategic thinking that Deepgram values across all functions, not just sales.

Is it worth applying to multiple roles at Deepgram simultaneously?

Ashby allows recruiters to see if a candidate has applied to multiple positions, so apply strategically rather than broadly. Applying to two closely related roles (e.g., two research positions in adjacent domains) is reasonable if your background genuinely spans both areas — just tailor each application. Applying to five unrelated positions signals unfocused interest and can dilute your candidacy. Choose the one or two roles where your experience is strongest, invest in customizing those applications thoroughly, and mention in your cover note that you're also interested in a secondary role if appropriate. Quality over quantity is the rule with Ashby — recruiters notice.

Sample Open Positions

Sources

Deepgram Careers Page — Deepgram
Deepgram Company Profile and Reviews — Glassdoor
Deepgram API Documentation and Developer Resources — Deepgram
Ashby ATS Platform Overview — Ashby