MongoDB’s Developer Experience organization is responsible for ensuring developers across every major language ecosystem can use MongoDB seamlessly, intuitively, and idiomatically. We build and maintain the rich set of client libraries and integrations that serve as the primary interfaces to the database, spanning more than ten programming languages and frameworks.

We’re looking for a Senior Product Manager for Python Developer Experience who will champion MongoDB’s relationship with the Python community, ensuring Python developers and data scientists have the best possible experience using MongoDB. You’ll define the strategy and roadmap for our Python driver, integrations (such as with Django, Flask and FastAPI), and tooling, informed by the needs of the ecosystem. You’ll collaborate closely with a world-class, globally distributed engineering team, but your focus is outward: understanding and serving Python developers where they are.

You’re a strong fit if you have hands-on experience building with Python and can translate developer pain points into clear, actionable product direction. You thrive at the intersection of code and product, care deeply about developer experience, and have a passion for learning, experimentation, and community engagement.

You will own the strategic vision, product strategy, and roadmap for how MongoDB serves Python developers—defining how our portfolio of client libraries, framework integrations, and ecosystem partnerships should evolve to meet both current developer expectations and future trends in the Python ecosystem. Your work will shape how developers build with MongoDB, ensuring a seamless, idiomatic experience that balances short-term developer needs with long-term platform differentiation and secures MongoDB’s place at the center of modern Python stacks such as the FARM stack.

You will collaborate closely with engineering, documentation, DevRel, and community teams to deliver a cohesive developer experience, and act as a champion for the Python ecosystem within MongoDB. You’ll stay ahead of trends, identify strategic opportunities, and make evidence-based decisions that drive adoption and delight.

As part of onboarding, you will build and document an application using MongoDB and a Python framework of your choice to gain firsthand insight into the developer experience. You’ll also engage directly with community forums, conferences, and open-source contributors to deepen your understanding, validate direction, and build trust with developers.

We are looking to speak to candidates who are based in Dublin for our hybrid working model.

About the team

We are a highly collaborative team of Product Managers, Engineers, Product Analysts, and Product Marketers all working together to make the experience of working with data easy and enjoyable for developers.

We are a distributed team; stretching from our offices in Dublin and NYC to other locations in  Europe, the US and Canada. Every now and then, we all meet in one place for project kickoffs, workshops, and other team events.

The ideal candidate for this role should have

• 3-5 years of product management experience with a track record of shipping developer-facing tools, integrations or APIs
• 3-5 years of commercial experience developing web applications in Python (the interviews for this position will include a live coding component meant to showcase your understanding of idioms, patterns, and evolving runtime environments) - including Django, FastAPI and Flask
• Experience with or exposure to Machine Learning and Data Science concepts and tools, including familiarity with common ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and data analysis libraries (e.g., Pandas, NumPy), as well as an understanding of data pipelines and model deployment
• Experience with AI development, including familiarity with Python AI frameworks and libraries such as Langchain, Langgraph, or LlamaIndex for deploying and managing AI solutions
• Ability to communicate sophisticated technical concepts simply and convincingly to a wide range of audiences
• Ability to distill customer use cases and requirements, write comprehensive business cases and execute on them
• Curiosity, a positive attitude, and a drive to continue learning
• Foster an inclusive and respectful work environment according to MongoDB's Core Values

Position Expectations

• Explore the problem space, build connections with your customer-base, interact with the users in the Python community, formulate the vision and the strategy and maintain the roadmap for your area, keeping it aligned with the company’s strategic priorities
• Deeply understand all aspects of the business — your job is to ensure a business outcome, not just product definition!
• Work closely with the product marketing and engineering teams to design, architect, implement and ship new capabilities of the MongoDB developer experience to delight users
• Collect and analyze data that will drive product decisions
• Work with thought leaders from the respective language communities, establish credibility, and weigh in discussions
• Keep your pulse on software engineering trends across language communities and advocate for new languages, frameworks etc  to be added to our portfolio
• Engage in various go to market activities such as collaborating on a marketing campaign, running a survey, or producing sales messaging

Success Measures

• In three months, you will have onboarded on the current MongoDB technologies & tools, and built an application with Python and MongoDB, putting it in public on Github; successfully triaged new issues with the engineering team, taken ownership of the existing roadmap and the product backlog; got to know the team (this team is globally distributed) and started building relationships inside the company
• In six months, you will have reviewed / refined existing user stories and JIRA issues, prioritized and started executing on them with your  engineering team; you will have also researched new and existing markets, identified some new trends and started their exploration in a methodical way
• In nine months, you have produced at least two GA releases of tier 1 drivers or integrations, several service releases, delighted users with new/improved experiences (you’ll need to define your metrics to measure customer success with your deliverables as well), identified new opportunities & refined your roadmap, contributed to other projects, presented to customers, user groups, and conferences, and gained strong support of your team and other stakeholders

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 4263289662

MongoDB’s Developer Experience organization is responsible for ensuring developers across every major language ecosystem can use MongoDB seamlessly, intuitively, and idiomatically. We build and maintain the rich set of client libraries and integrations that serve as the primary interfaces to the database, spanning more than ten programming languages and frameworks.

We’re looking for a Senior Product Manager for Python Developer Experience who will champion MongoDB’s relationship with the Python community, ensuring Python developers and data scientists have the best possible experience using MongoDB. You’ll define the strategy and roadmap for our Python driver, integrations (such as with Django, Flask and FastAPI), and tooling, informed by the needs of the ecosystem. You’ll collaborate closely with a world-class, globally distributed engineering team, but your focus is outward: understanding and serving Python developers where they are.

You’re a strong fit if you have hands-on experience building with Python and can translate developer pain points into clear, actionable product direction. You thrive at the intersection of code and product, care deeply about developer experience, and have a passion for learning, experimentation, and community engagement.

You will own the strategic vision, product strategy, and roadmap for how MongoDB serves Python developers—defining how our portfolio of client libraries, framework integrations, and ecosystem partnerships should evolve to meet both current developer expectations and future trends in the Python ecosystem. Your work will shape how developers build with MongoDB, ensuring a seamless, idiomatic experience that balances short-term developer needs with long-term platform differentiation and secures MongoDB’s place at the center of modern Python stacks such as the FARM stack.

You will collaborate closely with engineering, documentation, DevRel, and community teams to deliver a cohesive developer experience, and act as a champion for the Python ecosystem within MongoDB. You’ll stay ahead of trends, identify strategic opportunities, and make evidence-based decisions that drive adoption and delight.

As part of onboarding, you will build and document an application using MongoDB and a Python framework of your choice to gain firsthand insight into the developer experience. You’ll also engage directly with community forums, conferences, and open-source contributors to deepen your understanding, validate direction, and build trust with developers.

This role can be based out of our Dublin office or remotely in Ireland.

About the team

We are a highly collaborative team of Product Managers, Engineers, Product Analysts, and Product Marketers all working together to make the experience of working with data easy and enjoyable for developers.

We are a distributed team; stretching from our offices in Dublin and NYC to other locations in  Europe, the US and Canada. Every now and then, we all meet in one place for project kickoffs, workshops, and other team events.

The ideal candidate for this role should have

• 3-5 years of product management experience with a track record of shipping developer-facing tools, integrations or APIs
• 3-5 years of commercial experience developing web applications in Python (the interviews for this position will include a live coding component meant to showcase your understanding of idioms, patterns, and evolving runtime environments) - including Django, FastAPI and Flask
• Experience with or exposure to Machine Learning and Data Science concepts and tools, including familiarity with common ML frameworks (e.g., scikit-learn, TensorFlow, PyTorch) and data analysis libraries (e.g., Pandas, NumPy), as well as an understanding of data pipelines and model deployment
• Experience with AI development, including familiarity with Python AI frameworks and libraries such as Langchain, Langgraph, or LlamaIndex for deploying and managing AI solutions
• Ability to communicate sophisticated technical concepts simply and convincingly to a wide range of audiences
• Ability to distill customer use cases and requirements, write comprehensive business cases and execute on them
• Curiosity, a positive attitude, and a drive to continue learning
• Foster an inclusive and respectful work environment according to MongoDB's Core Values

Position Expectations

• Explore the problem space, build connections with your customer-base, interact with the users in the Python community, formulate the vision and the strategy and maintain the roadmap for your area, keeping it aligned with the company’s strategic priorities
• Deeply understand all aspects of the business — your job is to ensure a business outcome, not just product definition!
• Work closely with the product marketing and engineering teams to design, architect, implement and ship new capabilities of the MongoDB developer experience to delight users
• Collect and analyze data that will drive product decisions
• Work with thought leaders from the respective language communities, establish credibility, and weigh in discussions
• Keep your pulse on software engineering trends across language communities and advocate for new languages, frameworks etc  to be added to our portfolio
• Engage in various go to market activities such as collaborating on a marketing campaign, running a survey, or producing sales messaging

Success Measures

• In three months, you will have onboarded on the current MongoDB technologies & tools, and built an application with Python and MongoDB, putting it in public on Github; successfully triaged new issues with the engineering team, taken ownership of the existing roadmap and the product backlog; got to know the team (this team is globally distributed) and started building relationships inside the company
• In six months, you will have reviewed / refined existing user stories and JIRA issues, prioritized and started executing on them with your  engineering team; you will have also researched new and existing markets, identified some new trends and started their exploration in a methodical way
• In nine months, you have produced at least two GA releases of tier 1 drivers or integrations, several service releases, delighted users with new/improved experiences (you’ll need to define your metrics to measure customer success with your deliverables as well), identified new opportunities & refined your roadmap, contributed to other projects, presented to customers, user groups, and conferences, and gained strong support of your team and other stakeholders

About MongoDB

MongoDB is built for change, empowering our customers and our people to innovate at the speed of the market. We have redefined the database for the AI era, enabling innovators to create, transform, and disrupt industries with software. MongoDB’s unified database platform—the most widely available, globally distributed database on the market—helps organizations modernize legacy workloads, embrace innovation, and unleash AI. Our cloud-native platform, MongoDB Atlas, is the only globally distributed, multi-cloud database and is available across AWS, Google Cloud, and Microsoft Azure.

With offices worldwide and nearly 60,000 customers—including 75% of the Fortune 100 and AI-native startups—relying on MongoDB for their most important applications, we’re powering the next era of software.

Our compass at MongoDB is our Leadership Commitment, guiding how and why we make decisions, show up for each other, and win. It’s what makes us MongoDB. 

To drive the personal growth and business impact of our employees, we’re committed to developing a supportive and enriching culture for everyone. From employee affinity groups, to fertility assistance and a generous parental leave policy, we value our employees’ wellbeing and want to support them along every step of their professional and personal journeys. Learn more about what it’s like to work at MongoDB, and help us make an impact on the world!

MongoDB is committed to providing any necessary accommodations for individuals with disabilities within our application and interview process. To request an accommodation due to a disability, please inform your recruiter.

MongoDB is an equal opportunities employer.

Req ID: 4263289662

We’re looking for a machine learning engineer II in our Growth Platform engineering group. You’ll join a small and focussed team who will help us to understand our users better so we can drive engagement and growth, and to improve their user experience.

What you'll do:

• Develop and implement ML models to improve user targeting and personalization for growth initiatives
• Design and build scalable ML pipelines for data processing, model training, and deployment
• Collaborate with cross-functional teams to identify potential ML solutions for growth opportunities
• Conduct A/B tests to evaluate the performance of ML models and optimize their impact on key growth metrics
• Analyze large datasets to extract insights and inform decision-making for user acquisition and retention strategies
• Contribute to the development of our ML infrastructure, ensuring it can support rapid experimentation and deployment
• Stay up-to-date with the latest advancements in ML and recommend new techniques to enhance our growth efforts
• Participate in code reviews and collaborate with team members as needed
• Thoughtfully leverage AI tools to speed up design, coding, debugging, and documentation, while applying your own critical thinking to validate outputs and explain how you used AI in your workflow.
• Shape our AI-assisted engineering practices by sharing patterns, guardrails, and learnings with the team so we can safely increase our impact without compromising code quality, reliability, or candidate expectations.

What we're looking for:

• 3+ years of experience applying ML to real-world problems, preferably in a growth or user acquisition context
• Excellent communication skills and ability to work effectively in cross-functional teams 
• Strong problem-solving skills and ability to translate business requirements into technical solutions
• Strong programming skills in Python and experience with PyTorch
• Proficiency in data processing and analysis using tools like SQL, Spark, or Hadoop
• Experience with recommendation systems, user modeling, or personalization algorithms
• Familiarity with statistical analysis
• Experience using AI coding assistants and agentic tools as a force-multiplier, and equally comfortable solving problems from first principles when those tools aren’t available.
• Bachelor’s/Master’s degree in a relevant field or equivalent experience.
• Nice to have:
  • Experience with Natural Language Processing (NLP) to enhance user targeting and personalization strategies
  • Proficiency in data visualization techniques
  • Experience with cloud platforms (e.g., AWS) and containerization technologies (e.g., Docker, Kubernetes)
  • Contributions to open-source ML projects or research publications

Relocation Statement:

•  This position is not eligible for relocation assistance. Visit our PinFlex page to learn more about our working model.

In-Office Requirement Statement:

• We recognize that the ideal environment for work is situational and may differ across departments. What this looks like day-to-day can vary based on the needs of each organization or role.
• This role will need to be in the office for in-person collaboration 1-2 times per month and therefore needs to be in a commutable distance from one of the following offices: Dublin.

#LI-HYBRID 

#LI-JD1

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems
  
  
  

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-VIETNAM
#LI-BRAZIL
#LI-INDIA

The Opportunity

Our AI teams build highly available, low-latency microservices using modern, cloud-native technologies. This role sits within our broader AI organization and focuses on developing the platforms, services, and tooling that support AI-powered products — from inference and embeddings to APIs, data flows, and observability.

You’ll work in a fast-paced environment where reliability, performance, and usability matter just as much as innovation. While some squads work closer to inference pipelines and LLM tooling, others focus on platform foundations, troubleshooting and reliability, data systems, or observability — all critical to delivering AI in production at scale.

What You’ll Do

• Build, test, and deploy scalable microservices for AI-powered systems, including text and voice processing
  
  
• Design developer-friendly APIs, agents and internal tools that make AI easy to use across the Telnyx product ecosystem
  
  
• Contribute to AI inference, embeddings, and platform services that support real-time and low-latency workloads
  
  
• Optimize performance, reliability, and observability in production environments
  
  
• Collaborate closely with Product, Infrastructure, and ML teams to bring features from ideation to production
  
  
• Troubleshoot, debug, and support critical systems running in production
  
  
• Participate in code reviews and uphold high engineering and operational standards
  
  

Depending on the squad, your focus may lean more toward inference pipelines, platform foundations, observability, data systems, or production troubleshooting.

Who We’re Looking For

• Someone who has built something with cutting-edge AI tooling (something that has only become possible in the last 6 months, rolling from application date). It doesn't really matter what it is; we just want to know you are building and staying up to date.
  
  
• Strong understanding of async programming, concurrency, and parallel execution
  
  
• Experience with microservice-based systems
  
  
• Excellent communication skills and the ability to work effectively across teams
  
  

Nice to Haves

• Familiarity with LLM frameworks and tools (e.g. PyTorch, Transformers, DeepSpeed, vLLM)
  
  
• Experience with distributed computing frameworks such as Ray (Ray Core, Serve, Train)
  
  
• Exposure to cloud-native stacks (Docker, Kubernetes, Prometheus, Jaeger)
  
  
• Knowledge of LLM optimization techniques (e.g. quantization, speculative decoding)
  
  
• Background in Retrieval Augmented Generation (RAG) systems

How We Hire Across Our AI Teams

Our AI Chapter is made up of multiple squads, including:

• AI application & software engineering
  
  
• Platform & infrastructure foundations
  
  
• Troubleshooting, reliability, and production support
  
  
• Data, storage, and embeddings
  
  
• Observability and performance monitoring
  
  

We hire into a shared AI engineering pipeline. During interviews, we focus on core engineering skills, system design, and problem-solving ability. Final squad alignment happens later, based on:

• Your strengths and interests
  
  
• Team needs at the time
  
  
• Where you’ll have the biggest long-term impact
  
  

This means the exact focus of the role may vary by squad, but the core expectation remains the same: building reliable, scalable AI systems in production.

Why You’ll Love It Here

At Telnyx, we’re not just building products — we’re building the future of intelligent communication. Our TelnyxAI platform empowers developers and businesses to:

• Store and serve vector embeddings at scale
  
  
• Use open-source models with our hosted inference infrastructure
  
  
• Deploy multimodal AI features across text, voice, and storage seamlessly
  
  

You’ll have the autonomy to take ownership of meaningful projects, contribute ideas that shape the product roadmap, and collaborate with talented people who care deeply about impact, quality, and long-term thinking.

#LI-KG1
#LI-BRAZIL

The Impact You'll Drive

As a Senior ML Engineer (Speech Synthesis), you’ll be a founding member of the team building Telnyx’s next-generation speech synthesis systems. This is a greenfield opportunity — you’ll define the stack, architecture, and best practices for training and deploying state-of-the-art multilingual text-to-speech (TTS) models that power our voice AI agents.

You’ll build everything from distributed training pipelines to inference services that generate ultra-low-latency, lifelike voices across dozens of languages. Your work will bridge research and production — shaping how millions of people experience real-time conversational AI.

What You’ll Work On

• Own the stack from day one: Design and implement the ML training and inference pipelines for multilingual speech synthesis.
• Low-latency TTS: Engineer systems optimized for real-time, streaming speech generation with sub-100ms response targets.
• Train cutting-edge models: Build and fine-tune multilingual TTS systems using modern architectures — including LLM-based, diffusion, and flow-matching approaches.
• Massive-scale data processing: Develop pipelines for ingesting, aligning, and normalizing text, audio, and phonetic data across dozens of languages.
• Experimentation at scale: Run distributed training across multi-node GPU clusters, tracking results and iterating quickly.
• Cross-functional collaboration: Work with infrastructure and voice platform teams to deploy models that scale globally.
• Research meets production: Evaluate emerging techniques (LLM-guided synthesis, zero/few-shot voice cloning, full-duplex modeling) and bring them to life in production-grade systems.

What You’ll Work With

• Infrastructure: Docker, Kubernetes, Ray, Kubeflow, MLflow, Weights & Biases
• Data Systems: Kafka, Redis, PostgreSQL, Parquet
• You’ll define it: You’ll help select and implement the stack that supports distributed training, data processing, and inference for global deployment.

What We’re Looking For

• 6+ years of experience in machine learning or speech systems engineering
• Hands-on expertise with neural TTS, speech synthesis, or adjacent areas (ASR, voice cloning, multilingual modeling)
• You’ve obsessed over one or two hard problems, whether it’s building multilingual TTS from noisy data, teaching LLMs to speak, designing self-supervised audio encoders, or making diffusion models run in real time.
• Experience with LLM-based approaches to speech synthesis or prosody control
• Strong proficiency in Python and PyTorch
• Ability to deploy models efficiently (ONNX, TensorRT)
• Experience leading small teams and defining technical direction or team executables
• Production mindset: You build systems that run fast, stay stable, and are easy to maintain

Why Telnyx

You’ll be joining a company where voice, infrastructure, and AI converge. Telnyx is building the foundation for real-time, intelligent global communications — and your work on multilingual TTS will be at the core of that vision.



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