As an Enterprise Sales Engineer, you will provide technical expertise through sales presentations, product demonstrations, and supporting technical evaluations (POVs). Sales Engineers help qualify and close opportunities with customers and partners and have a voice with the product team to help prioritize features based on input from customers, competitors, and partners.

At Datadog, we place value in our office culture - the relationships and collaboration it builds and the creativity it brings to the table. We operate as a hybrid workplace to ensure our Datadogs can create a work-life harmony that best fits them.

What You’ll Do:

• Partner with the Sales team to articulate the overall Datadog value proposition, vision and strategy to customers
• Own technical engagement with customers during the trial phase. Communicate Datadog’s value based on activities and work with customers on any identified issues or concerns to successful conclusion
• Technically close complex opportunities through advanced competitive knowledge, technical skill, and credibility
• Deliver product and technical briefings / presentations to potential clients
• Maintain accurate notes and feedback in CRM regarding customer input both wins and losses
• Proactively engage and communicate with customers and Datadog business/technical teams regarding product feedback and competitive landscape

Who You Are:

• Passionate about educating customers on observability risks that are meaningful to their business, and able to build and execute an evaluation plan with a customer
• Someone with strong written and oral communication skills. This role requires an ability to understand and articulate both the business benefits (value proposition) and technical advantages of our offering
• Experienced in programming/scripting with any of the following: Java, Python, Ruby, Go, Node.JS, PHP, and .NET etc.
• Someone with a minimum of 3+ years in a Sales Engineering or DevOps Engineering role
• Able to sit up to 4 hours, traveling to and from client sites 
• Able to travel via auto, train or air up to 45% of the time

Datadog values people from all walks of life. We understand not everyone will meet all the above qualifications on day one. That's okay. If you’re passionate about technology and want to grow your skills, we encourage you to apply.

Benefits and Growth: 

• Best-in-breed onboarding
• Generous global benefits
• Intra-departmental mentor and buddy program for in-house networking
• New hire stock equity (RSUs) and employee stock purchase plan (ESPP)
• Continuous professional development, product training, and career pathing
• An inclusive company culture, able to join our Community Guilds and Inclusion Talks

Benefits and Growth listed above may vary based on the country of your employment and the nature of your employment with Datadog.

#LI-Remote

Mission

Speechify is the easiest way to listen to the world’s information. Articles on the web, documents in the cloud, books on your phone. We absorb it all and let you listen to it at your desk, on the go, at your own speed, and with tools that make learning easier, deeper, and faster.

What streaming services have done for audio entertainment, we’re doing for audio information. And whatever we’re doing seems to be working. We’re #1 in our category, and experiencing exponential growth.

Overview

We're looking for a Senior Software Engineer to join our Core Experiences Team. This team builds and maintains the foundational services and SDKs that power Speechify’s product experience across platforms. It's a critical role for someone who enjoys working at the intersection of product and infrastructure, thinks strategically, and is passionate about designing clear, reliable APIs and simple systems that directly enhance the user experience.

What You’ll Do

• Collaborate with Speechify’s Product Teams to scope projects, find ways to reduce scope to get faster feedback from customers, navigate the integration/UX tradeoffs relevant to different product teams, and deliver solutions via our cross-platform SDK
• Optimize existing functionality to ship things like faster loading and more intelligent parsing by designing more efficient abstractions and improving our algorithms
• Ship cloud functions, lightweight backend services, and jobs using Kotlin

An Ideal Candidate Should Have

• Systems thinking. You know that optimizing a system requires end-to-end design, and you believe simplicity is valuable.
• Speed. You work quickly to generate ideas and options and know how to decide which things can ship now and what things need time
• Focus. We’re a high-growth startup with a busy, remote team. You know how and when to engage or be heads down
• Collaboration. You know how to inspire, play, and negotiate with opinionated designers, marketers, and PMs
• Preferred Tech Stack:
  • Kotlin Multiplatform (Java experience is OK but role is Kotlin Multiplatform) 
  • Prior experience with GCP is a plus

What We Offer

• A fast-growing environment where you can help shape the company and product.
• An entrepreneurial-minded team that supports risk, intuition, and hustle.
• A hands-off management approach so you can focus and do your best work.
• An opportunity to make a big impact in a transformative industry.
• Competitive salaries, a friendly and laid-back atmosphere, and a commitment to building a great asynchronous culture.
• Opportunity to work on a life-changing product that millions of people use.
• Build products that directly impact and support people with learning differences like dyslexia, ADD, low vision, concussions, autism, and more.
• Work in one of the fastest growing sectors of tech, the intersection of artificial intelligence and audio.

Think you’re a good fit for this job? 

Tell us more about yourself and why you're interested in the role when you apply.
And don’t forget to include links to your portfolio and LinkedIn.

Not looking but know someone who would make a great fit? 

Refer them! 

Speechify is committed to a diverse and inclusive workplace. 

Speechify does not discriminate on the basis of race, national origin, gender, gender identity, sexual orientation, protected veteran status, disability, age, or other legally protected status.

FEQ427R83

At Databricks, our core principles are at the heart of everything we do; creating a culture of proactiveness and a customer-centric mindset guides us to create a unified platform that makes data science and analytics accessible to everyone. We aim to inspire our customers to make informed decisions that push their business forward. We provide a user-friendly and intuitive platform that makes it easy to turn insights into action and fosters a culture of creativity, experimentation, and continuous improvement. You will be an essential part of this mission, using your technical expertise to demonstrate how our Data Intelligence Platform can help customers solve their complex data challenges. You'll work with a collaborative, customer-focused team who values innovation and creativity, using your skills to create customized solutions to help our customers achieve their goals and guide their businesses forward. Join us in our quest to change how people work with data and make a better world!

The impact you will have: 

• Form successful relationships with clients throughout your assigned territory to provide technical and business value in collaboration with an Account Executive and a Senior Solutions Architect.
• Gain excitement from clients about Databricks through hands-on evaluation and Spark programming, integrating with the wider cloud ecosystem and 3rd party applications.
• Contribute to building the Databricks technical community through engagement at workshops, seminars, and meet-ups.
• Become a Big Data Analytics advisor on aspects of architecture and design.
• Support your customers by authoring reference architectures, how-tos, and demo applications.
• Develop both technically and in the pre-sales aspect with the goal of becoming an independently operating Solutions Architect.

What we look for:

• Familiarity working with clients, creating a narrative, answering customer questions, aligning the agenda with important interests, and achieving tangible outcomes.
• Ability to independently deliver a technical proposition, identify customers' pain-points, and explain important areas for business value to develop a trusted advisor skillset.
• Code in a core programming language such as Python, Java, or Scala.
• Knowledgeable in a core Big Data Analytics domain with some exposure to advanced proofs-of-concept and an understanding of a major public cloud platform.
• Experience diving deeper into solution architecture and design.

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Research Engineer to join the Machine Learning Science (MLS) team, within the Computational Science department. The ideal candidate has a strong knowledge in designing and building deep learning (DL) pipelines, and expertise in creating reliable, scalable artificial intelligence/machine learning (AI/ML) systems in a cloud environment. 

The MLS team at Freenome develops DL models using massive-scale genomic data that presents significant challenges for current training paradigms. The Senior Machine Learning Research Engineer will primarily be responsible for developing and deploying the infrastructure needed to support development of such DL models: enabling distributed DL pipelines, optimizing hardware utilization for efficient training, and performing model optimizations. As part of an interdisciplinary R&D team, they will work in close collaboration with machine learning scientists, computational biologists and software engineers to accelerate the development of state-of-the-art ML/AI models and help Freenome achieve its mission of reducing cancer mortality via accessible early detection.

The role reports to the Director of Machine Learning Science. This can be a hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Implement and refine DL pipelines on distributed computing platforms enhancing the speed and efficiency of DL operations including model training, data handling, model management, and inference.
• Collaborate closely with ML scientists and software engineers to understand current challenges and requirements and ensure that the DL model development pipelines you create are perfectly aligned with scientific goals and operational needs.
• Continuously monitor, evaluate, and optimize DL model training pipelines for performance and scalability.
• Stay up to date with the latest advancements in AI, ML, and related technologies, and quickly learn and adapt new tools and frameworks, if necessary.
• Develop and maintain robust and reproducible DL pipelines that guarantee that DL pipelines can be reliably executed, maintaining consistency and accuracy of results.
• Drive performance improvements across our stack through profiling, optimization, and benchmarking. Implement efficient caching solutions and debug distributed systems to accelerate both training and evaluation pipelines.
• Act as a bridge facilitating communication between the engineering and scientific teams, documenting and sharing best practices to foster a culture of learning and continuous improvement.

Must haves:

• MS or equivalent experience in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Software Engineering, with an emphasis on AI/ML theory and/or practical development.
• 5+ years of post-MS industry experience working on developing AI/ML software engineering pipelines.
• Proficiency in a general-purpose programming language: Python (preferred), Java, Julia, C, C++, etc.
• Strong knowledge of ML and DL fundamentals and hands-on experience with machine learning frameworks such as PyTorch, TensorFlow, Jax or Scikit-learn.
• In-depth knowledge of scalable and distributed computing platforms that support complex model training (such as Ray or DeepSpeed) and their integration with ML developer tools like TensorBoard, Wandb, or MLflow.
• Experience with cloud platforms (e.g., AWS, Google Cloud, Azure) and how to deploy and manage AI/ML models and pipelines in a cloud environment.
• Understanding of containerization technologies (e.g., Docker) and computing resource orchestration tools (e.g., Kubernetes) for deploying scalable ML/AI solutions.
• Proven track record of developing and optimizing workflows for training DL models, large language models (LLMs), or similar for problems with high data complexity and volume.
• Experience managing large datasets, including data storage (such as HDFS or Parquet on S3), retrieval, and efficient data processing techniques (via libraries and executors such as PyArrow and Spark).
• Proficiency in version control systems (e.g., Git) and continuous integration/continuous deployment (CI/CD) practices to maintain code quality and automate development workflows.
• Expertise in building and launching large-scale ML frameworks in a scientific environment that supports the needs of a research team.
• Excellent ability to work effectively with cross-functional teams and communicate across disciplines. 
  

Nice to haves:

• Experience working with large-scale genomics or biological datasets.
• Experience managing multimodal datasets, such as combinations of sequence, text, image, and other data.
• Experience GPU/Accelerator programming and kernel development (such as CUDA, Triton or XLA).
• Experience with infrastructure-as-code and configuration management.
• Experience cultivating MLOps and ML infrastructure best practices, especially around reliability, provisioning and monitoring.
• Strong track record of contributions to relevant DL projects, e.g. on github.
  

Benefits and additional information:

The US target range of our base salary for new hires is $161,925 - $227,325 You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-REMOTE

About this opportunity:

At Freenome, we are seeking a Senior Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, and the ability to thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
• Build models that achieve high accuracy and that generalize robustly to new data.
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
• Take a mindful, transparent, and humane approach to your work.

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 3+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise, demonstrated by research publications or industry achievements, in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
• Experience in NGS data analysis and bioinformatic pipelines.
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.

Benefits and additional information:

The US target range of our base salary/hourly rate for new hires is $173,775 - $246,750. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-HYBRID

About this opportunity:

At Freenome, we are seeking a Staff Machine Learning Scientist to help grow the Machine Learning Science team, within the Computational Science department. The ideal candidate has a strong knowledge of artificial intelligence (AI), including machine learning (ML) fundamentals and extensive experience with deep learning (DL) methods, a track record of successfully using these methods to answer complex research questions, the ability to drive independent research and thrive in a highly cross-functional environment.

They will be responsible for the development of algorithms for early, blood-based detection tests for cancer. They will build on a foundation of ML/DL and statistical skills to develop models for identifying molecular signals from blood. They will also work with computational biologists, molecular biologists and ML engineers to design and drive research experiments, and will have a significant impact on the continued growth of an organization dedicated to changing the entire landscape of cancer.

The role reports to the Director, Machine Learning Science. This role can be a Hybrid role based in our Brisbane, California headquarters (2-3 days per week in office), or remote.

What you’ll do:

• Independently pursue cutting edge research in AI applied to biological problems (including cancer research, genomics, computational biology, immunology, etc.).
  
• Build new models or fine-tune existing models to identify biological changes resulting from disease.
  
• Build models that achieve high accuracy and that generalize robustly to new data.
  
• Apply contemporary interpretability techniques to provide a deeper understanding of the underlying signal identified by the model, ideally suggesting potential biological mechanisms.
  
• Work closely with ML Engineering partners to ensure that Freenome’s computational infrastructure supports optimal model training and iteration.
  
• Take a mindful, transparent, and humane approach to your work.
  

Must haves:

• PhD or equivalent research experience with an AI emphasis and in a relevant, quantitative field such as Computer Science, Statistics, Mathematics, Engineering, Computational Biology, or Bioinformatics.
• 6+ years of postdoc or post-PhD industry experience achieving impactful results using relevant modeling techniques.
• Expertise demonstrated by research publications or industry achievements, in driving independent research in applied machine learning, deep learning and complex data modeling.
• Practical and theoretical understanding of fundamental ML models like generalized linear models, kernel machines, decision trees and forests, neural networks, boosting and model aggregation.
• Practical and theoretical understanding of DL models like large language models or other foundation models.
• Extensive experience with training paradigms like supervised learning, self-supervised learning, and contrastive learning.
• Proficient in current state of the art in ML/DL approaches in different domains, with an ability to envision their applications in biological data.
• Proficiency in a general-purpose programming language: Python, R, Java, C, C++, etc.
• Proficiency in one or more ML frameworks such as; Pytorch, Tensorflow and Jax; and ML platforms like Hugging Face.
• Experience in ML analysis and developer tools like TensorBoard, MLflow or Weights & Biases.
• Excellent ability to communicate across disciplines, work collaboratively, and make progress in smaller steps via experimental iterations.
• Proficient at productive cross-functional scientific communication and collaboration with software engineers and computational biologists.
• A passion for innovation and demonstrated initiative in tackling new areas of research.

Nice to haves:

• Deep domain-specific experience in computational biology, genomics, proteomics or a related field.
  
• Experience in building DL models for genomic data, with knowledge of state-of-the-art DNA foundation models.
  
• Experience in NGS data analysis and bioinformatic pipelines.
  
• Experience with containerized cloud computing environments such as Docker in GCP, Azure, or AWS.
  
• Experience in a production software engineering environment, including the use of automated regression testing, version control, and deployment systems.
  

Benefits and additional information:

The US target range of our base salary for new hires is $199,675.00 - $283,500.00. You will also be eligible to receive equity, cash bonuses, and a full range of medical, financial, and other benefits depending on the position offered.  Please note that individual total compensation for this position will be determined at the Company’s sole discretion and may vary based on several factors, including but not limited to, location, skill level, years and depth of relevant experience, and education. We invite you to check out our career page @ freenome.com/job-openings/ for additional company information.  

Freenome is proud to be an equal-opportunity employer, and we value diversity. Freenome does not discriminate on the basis of race, color, religion, marital status, age, national origin, ancestry, physical or mental disability, medical condition, pregnancy, genetic information, gender, sexual orientation, gender identity or expression, veteran status, or any other status protected under federal, state, or local law.

Applicants have rights under Federal Employment Laws.  

• Family & Medical Leave Act (FMLA)
• Equal Employment Opportunity (EEO)
• Employee Polygraph Protection Act (EPPA)

#LI-HYBRID