Задачи:
— разработка решений на Python для обработки и преобразования данных;
— построение автоматизированных workflow с использованием Apache Airflow, включая планирование, управление зависимостями, мониторинг и обработку ошибок;
— создание и поддержка Docker-окружений для воспроизводимого выполнения задач;
— интеграция источников данных, API и вычислительных инструментов в автоматизированные процессы;
— повышение надёжности, масштабируемости и сопровождаемости пайплайнов через тестирование, логирование и оптимизацию производительности;
— сотрудничество с инженерными и научными командами.
Требования:
— сильные навыки программирования на Python и опыт разработки решений для обработки данных;
— практический опыт работы с Apache Airflow или аналогичными оркестраторами;
— опыт с Docker и контейнеризацией;
— практический опыт с PostgreSQL и/или Snowflake;
— понимание ETL/ELT-процессов, интеграции данных и автоматизации workflow;
— умение разбираться в сбоях пайплайнов и строить надёжные сопровождаемые решения.
Плюсом будут:
— опыт с другими оркестраторами;
— знакомство с AWS;
— опыт проектирования и интеграции API;
— знание Kubernetes и GitOps;
— опыт разработки AI-приложений;
— бэкграунд в life sciences, вычислительной химии, биоинформатике или поиске лекарств.
Условия:
— работа удалённо;
— полная занятость;
— сотрудничество по B2B-контракту с выплатами в USD или EUR либо по трудовому договору.
We're looking for a hands-on AI Engineer to take ownership of the architecture and development of our autonomous agent system. You'll lead the technical direction of the platform, building multi-agent orchestration systems, self-improving agent harnesses, and AI-powered backend services.
Location: Chicago, IL or Remote
CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the
multi-trillion-dollar
insurance economy
,
creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and
seamlessly. We’re
pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair
journey. Through
purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at
www.cccis.com
.
The Role
As a Senior AI Engineer you will own LLM-powered systems and agentic workflows for our customers. These systems automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with a measured accuracy you can defend as models change and usage grows. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system architecture, code quality, security, and the debugging nobody else gets to the bottom of. You own a product area end to end and define the eval bar it ships against.
Salary range is:
$180,000 - 225,000
This position is bonus eligible.
Key Responsibilities:
Own the delivery of LLM-powered systems in Python and TypeScript, from an ambiguous customer problem, scoped with product managers and data scientists, through production operation.
Set the evals and guardrails strategy for your area: what gates a release, what production signals the team watches, and how a change is simulated against historical claims before it ships.
Raise the bar for how the team works with agentic coding tools: sharpen the specifications, instruction files, hooks, and permission policies they run under, and hold generated code to the same review standard before it merges.
Design the NLP pipelines that turn unstructured claim data into structured data customers can act on, choosing where semantic search, classical NLP, or an LLM fits.
Build and operate durable, event-driven, multi-tenant systems in which agents run as steps inside deterministic workflows, designing their failure modes, replay semantics, and cost profile before they show up under load.
Own tracing and audit for your area: every model call and agent step recorded, so any recommendation can be reconstructed and cited back to its sources by on-call and auditors alike.
Set the privacy and security baseline every system in your area starts from: tenant isolation, least-privilege access for agents and their tools, redaction, retention, and what data may reach a model provider.
Author the design documents for complex systems to get feedback and buy-in, review other engineers' designs and code with the same care, and mentor the engineers in your area.
Take part in a shared on-call rotation for the systems you own.
Requirements:
6+ years of professional software engineering experience, including an LLM-powered system you architected, shipped to external customers, and carried through at least one model or prompt migration.
Python and TypeScript at the level of setting a team's conventions: the async model, typing strictness, and test strategy for a shared codebase, plus a performance problem you profiled and fixed.
An evals and guardrails strategy you set for a product area others built in: where human approval was required, and how production corrections re-entered the evals.
A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work, plus changes you turned back, and why.
Pipelines you designed that blend LLMs, semantic search, and classical NLP, including a retrieval design you can defend and a case where a classical technique beat an LLM on cost, latency, or reliability.
Durable, event-driven systems you designed with deterministic orchestration around non-deterministic model steps: compensating actions, idempotency, backpressure, and event-sourced replay.
Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made.
Systems architected and operated on Azure or AWS, with CI/CD and infrastructure as code, and hands-on time with a durable workflow engine such as Temporal or the Durable Task Scheduler.
Technical design documents you have authored for systems that span more than one team, used to get feedback and buy-in before building, and that those teams then built to.
Clear writing and discussion for technical and non-technical audiences: drawing out a customer's real problem and explaining the trade-offs back to them.
Even Better if You Have:
React and TypeScript experience, so you can deliver a full-stack feature end to end, especially chat, streaming, and citation-heavy AI experiences.
Experience with agent frameworks, LangGraph, PydanticAI, and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices.
Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing.
Experience designing A/B tests for AI features.
Exposure to the insurance, claims, or automotive repair domains.
What Success Looks Like:
In your first six months, every model change in your area is gated by evals you designed, regressions are caught before a customer sees them, and you can show the accuracy number held or moved.
You are trusted with the high-stakes, ambiguous problems, and you turn them into a roadmap, a shipped system, and a number you can put in front of a customer.
You are energized by what agentic coding tools make possible. Your team ships more than its headcount suggests, and your specifications and reviews are why the output survives production.
You have a passion for systems that last: the ones you design have their failure modes understood in advance, and when one fails anyway, the trace says exactly where.
Privacy and security reviews of systems in your area find nothing that was not already designed in.
Standards you set for evals, reviews, and design documents outlive the project they started on.
Engineers you mentor ship LLM-powered features with evals and guardrails in place without your direct involvement.
You enjoy getting a product manager, a data scientist, and a customer's team into one room and coming out with a single agreed scope, and you can argue a position without needing to win it.
You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued.
Interview Policy & Privacy Notice:
A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available
HERE
.
About CCC's Commitment to Employees:
CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most.
At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success.
CCC offers competitive compensation and benefits to support you and your families, including:
401K Match
Paid time off
Annual Incentive Plan Performance Bonus
Comprehensive health insurance
Adoption Assistance
Tuition Reimbursement
Wellness Programs
Stock Purchase Plan options
Employee Resource Groups
For more information about our benefits, please check out our
careers site
.
Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture
here
Location: Chicago, IL or Remote
CCC Intelligent Solutions Inc. (CCC) is a leading cloud platform for the
multi-trillion-dollar
insurance economy
,
creating intelligent experiences for insurers, repairers, automakers, part suppliers, and more. At CCC, we’re making life just work by empowering more than 35,000 businesses with industry-leading technology to get drivers back on the road and to health quickly and
seamlessly. We’re
pushing boundaries with innovative AI solutions that simplify and enhance the claims and repair
journey. Through
purposeful innovation and the strength of its connections, CCC technologies empower the people and industry relied upon to keep lives moving forward when it matters most. Learn more about CCC at
www.cccis.com
.
The Role
As an AI Engineer you will build and ship LLM-powered features and agentic workflows for our customers. These features automate the routine parts of a claim and guide customers on the rest, so they have to earn that trust with measured accuracy, not a convincing demo. Agents run as steps inside deterministic workflows, and privacy and security are design baselines, not review gates. Agentic coding tools are how you move fast. What you add is what they are worst at: system design, security, and hard debugging. You own features end to end.
Salary range is:
$170,000 - 195,000
This position is bonus eligible.
Key Responsibilities:
Ship LLM-powered features and agentic workflows in Python and TypeScript, from a problem scoped with product managers and data scientists through production traffic, and help set the metrics you will be measured against.
Write the evals, guardrails, and feedback loops that make your features trustworthy, and hold them to explicit token and latency budgets.
Use agentic coding tools every day, and own the review of what they produce: catch the correctness, security, and design problems in generated code before you open the pull request.
Maintain and extend the NLP pipelines that turn unstructured claim data into structured data customers can act on, blending semantic search, classical NLP, and LLMs.
Build and operate durable, event-driven services in which agents run as steps inside deterministic workflows, with checkpointed model outputs so a retry does not re-invoke a completed LLM step.
Trace every model call and agent step so a recommendation can be reconstructed and audited, with citations back to the source documents, and wire that tracing into your alerts.
Model and query claims data across relational, document, and graph stores.
Design privacy and security in from the start: tenant isolation, least-privilege access for agents and their tools, and a clear rule for what data may reach a model provider.
Write a technical design document before any significant change, and use it to get feedback and buy-in from the team before you build.
Take part in a shared on-call rotation for the services you build.
Requirements:
3+ years of professional software engineering experience, including at least one LLM-powered feature you shipped and then operated in production.
Python and TypeScript: typed, tested, async code in both, and real depth in one.
Evals you have designed for LLM output, plus guardrails you have shipped.
A clear account of how you constrain an agentic coding tool's context and verify its output, from daily use of Claude Code, Cursor, GitHub Copilot, or similar on production work.
Pipelines that blend LLMs with semantic search and classical NLP: structured output, tool calling, embedding-based retrieval, and a case where a classical technique beat an LLM.
Services built on message- or event-driven architectures, including long-running workflows with retries, idempotent handlers, and event-sourced state, plus an LLM or agent step you ran inside one.
Data modeling and development across relational, document, and graph databases such as PostgreSQL, MongoDB, and Neo4j, including when each type fits and the partition-key, consistency, and tenant-isolation calls you made.
Backend services built and operated on Azure or AWS, and exposure to a durable workflow engine such as Temporal or the Durable Task Scheduler.
Technical design documents you have written to get feedback and buy-in from a team before building, and that the team then built to.
Clear writing and discussion for technical and non-technical audiences, and code review you can give as well as take.
Even Better if You Have:
React and TypeScript experience, so you can deliver a full-stack feature end to end. Chat, streaming, and citation-heavy AI experiences especially.
Experience with CI/CD pipelines and infrastructure as code such as Terraform or Bicep.
Experience with agent frameworks, LangGraph and the Microsoft Agent Framework among them, and with the ways agents reach their tools: the Model Context Protocol (MCP), the Agent2Agent (A2A) protocol, command-line tools, and microservices.
Experience with LLM observability and evaluation tooling such as LangSmith, Arize, or Braintrust, and with OpenTelemetry-based tracing.
Experience designing A/B tests for AI features, or what-if simulations that replay historical claims through a proposed change before it ships.
Exposure to the insurance, claims, or automotive repair domains.
What Success Looks Like:
In your first six months you ship an LLM-powered feature, its evals run in CI, and you can name the metric it moved.
When a model migration or prompt change causes a regression, the evals you wrote catch it before a customer does.
You take ownership from concept to production with light direction, asking the right questions early.
You care that things hold up: the services you build survive retries, partial failures, and model migrations without incidents a customer can see.
When something goes wrong in production, the trace tells you which step and which model call, and you can show an auditor the same thing.
Privacy and security reviews of your features find nothing that was not already designed in.
You enjoy the craft, and it shows: engineers pick up your patterns without being told to.
You enjoy the back-and-forth that gets a feature scoped, and you can argue a position without needing to win it.
You embrace our ambitious, collaborative, and empathetic values, and you like problems where the answer has to be measured rather than argued.
Interview Policy & Privacy Notice:
A video interview is required for this position. Video interviews are transcribed. Transcriptions are retained and may be reviewed by CCC and our recruiters. Candidates are not permitted to use generative AI or automated assistance during the interviews unless explicitly allowed by the interview team for a specific exercise. Our Job Applicant Privacy Notice is available
HERE
.
About CCC's Commitment to Employees:
CCC Intelligent Solutions understands that our employees play an integral role in our vision to shape a world where life just works. Our team is defined by our values of Integrity, Customer-Focus, Innovation, Inclusion & Diversity, Tenacity, and Connection. Through diverse perspectives, purposeful innovation, and the strength of connections, our technologies empower the people and industry relied upon to keep lives moving forward when it matters most.
At CCC, together everyone can thrive as we innovate and collaborate, creating employee experiences that just work. We are committed to providing opportunities for our people to make real-life impacts, advance in their careers, and contribute to CCC’s success.
CCC offers competitive compensation and benefits to support you and your families, including:
401K Match
Paid time off
Annual Incentive Plan Performance Bonus
Comprehensive health insurance
Adoption Assistance
Tuition Reimbursement
Wellness Programs
Stock Purchase Plan options
Employee Resource Groups
For more information about our benefits, please check out our
careers site
.
Here, you belong. You are seen, valued, and respected. We celebrate you for who you are and all you bring. Every voice is heard and is important to our success. You can hear what employees have to say about our culture
here
Location: Texas
Vectra® is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises.
The Vectra AI Platform delivers integrated signal across public cloud, SaaS, identity, and data center networks in a single platform. Powered by patented Attack Signal Intelligence, it empowers security teams to rapidly prioritize, investigate and respond to the most advanced cyber-attacks. With 35 patents in AI-driven threat detection and the most vendor references in MITRE D3FEND, organizations worldwide rely on the Vectra AI to move at the speed and scale of hybrid attackers. For more information, visit www.vectra.ai.
About Vectra AI
Vectra AI is the leader in AI-driven threat detection and response for hybrid and multi-cloud enterprises. The Vectra AI Platform brings together signal across public cloud, SaaS, identity, and data center networks to help security teams prioritize, investigate, and respond to advanced cyber-attacks.
The Role
Vectra AI is building a proactive, intelligent customer experience model that helps customers deploy, adopt, realize value, and expand with less dependency on manual intervention. These are the next steps in our customer experience that pair both human touch and automated enablement for our customers. The Customer AI & Automation Engineer will create the technical foundation that makes this model scalable, reliable, and measurable.
The Customer AI & Automation Engineer designs, builds, tests, and operates the workflows, integrations, and AI agents that power customer journeys across Salesforce, HubSpot, Pendo, enablement and product signals. This is a hands-on builder role for someone who combines systems thinking, data fluency, and practical business judgment.
The role supports Technical Account Managers (TAMs), Sales Engineers (SEs) responsible for post-sales account management, Professional Services (PS), Technical Support, and broader Digital Success initiatives.
Your Impact
Build and
maintain
customer lifecycle workflows across HubSpot, Salesforce, Pendo, and connected customer systems.
Design and operationalize AI agents for journey operations, signal detection, next-best-action recommendations, support guidance, and customer insight.
Translate requirements from Lifecycle Strategy, Customer Success, Support, SE, Product, Enablement, and Marketing into scalable automation and orchestration logic.
Technical Account Management: Automate account health preparation, technical success plan updates, recurring health checks, action tracking, and customer review preparation.
SE post-sales account management: Support technical account oversight, deployment and adoption reviews, product
utilization
analysis, technical risk identification, and follow-
through on
customer actions.
Professional Services: Streamline onboarding, deployment planning, readiness checks, project updates, and delivery documentation.
Technical Support: Improve case triage, troubleshooting, knowledge retrieval, and
resolution
workflows.
Digital Success: Build scalable onboarding, adoption guidance, customer health monitoring, and proactive outreach workflows.
Develop integrations and data flows that connect customer, product, support, engagement, and enablement signals.
Establish testing, QA, monitoring, exception handling, observability, and rollback procedures for
automations
and AI-enabled workflows.
Create operational reporting that surfaces journey enrollment, workflow health, drop-offs, exceptions, adoption signals, and agent performance.
Support the Customer Lifecycle Council with technical feasibility assessments, implementation estimates, and evidence on what is working or breaking.
Map customer journeys and internal processes, including handoffs between teams, and prioritize use cases based on customer impact, effort saved, feasibility, and business value.
Integrate knowledge platforms and internal product systems into agent workflows using APIs and orchestration tools.
Define clear operational ownership and human approval steps for agent actions, supported by audit trails and data protection controls.
Improve production workflows using feedback and usage data; document solutions and train teams to use and
maintain
them.
What You Will Bring
Demonstrated experience designing, building, deploying, and operating production-scale AI agents using both OpenAI GPT and Anthropic Claude models.
Hands-on experience selecting and orchestrating models for different tasks, including tool use, retrieval, structured outputs, workflow execution, evaluation, observability, permissions, and human escalation.
Proven ability to move agents beyond prototype stage into reliable, governed enterprise use cases with measurable business outcomes.
Experience building complex workflow automation and systems integrations in a customer-facing, revenue, marketing operations, customer operations, or product operations environment.
Strong analytical and troubleshooting skills, with the ability to trace a
customer
outcome through data, systems, workflow logic, and operational ownership.
A disciplined approach to testing, data quality, permissions, exception handling, and change management.
Ability to translate ambiguous business requirements into simple, scalable technical solutions and communicate clearly across technical and non-technical teams.
Proficiency
in Python or JavaScript/TypeScript and experience working with webhooks and structured data.
Hands-on experience with prompt design and retrieval-augmented generation.
Preferred Qualifications
Experience
operating
multi-model agent environments, including practical knowledge of GPT and Claude strengths, limitations, cost, latency, safety, and evaluation considerations.
Experience with customer lifecycle, digital customer success, product-led growth, or customer marketing motions.
Familiarity with customer health, telemetry, product usage, support, and enablement data.
Experience working in B2B SaaS, cybersecurity, or another complex enterprise technology environment.
Practical experience with Salesforce, HubSpot, Pendo, support platforms, CDPs or data warehouses, APIs, and automation tools.
Familiarity with Jira, MuleSoft, Forethought, or comparable platforms.
Understanding of
technical account management, post-sales account management, implementation, and service delivery processes.
Success Measures
Reduced manual effort across targeted workflows.
Shorter cycle times and faster customer onboarding and time to value.
Increased product adoption and effective digital engagement.
Earlier identification and follow-through on customer risks.
Improved efficiency and account coverage for TAMs and post-sales SEs.
Reliable agent execution and measurable customer experience improvements.
Vectra provides a comprehensive total rewards package
that
supports
the
financial,
physical, mental and overall health of
our employees
and their families.
Compensation includes competitive base pay, incentive pla
n eligibility, and participation in the employee equity plan (stock options).
Specific benefits
offered
var
ies
by location, but commonly in
clude
health care insurance
,
income protection
/ life insurance
,
access to retirement
savings
plans, behavioral &
emotional
wellness
services
, generous time away from work,
and
a comprehensive employee recognition program.
Vectra is committed to creating a diverse environment and is proud to be an equal opportunity employer.
We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status.
We are hiring ML inference and serving experts to turn real, paid tasks from their jobs into expert-level Terminal-Bench challenges. ⢠Design expert-level Terminal-Bench tasks that turn real, paid ML inference work from your own experience into challenges an AI agent must solve end to end.
Location: Remote - India
Who we are
At Twilio, we’re shaping the future of communications, all from the comfort of our homes. We deliver innovative solutions to
hundreds of thousands of businesses
and empower millions of developers worldwide to craft personalized customer experiences.
Our dedication to
remote-first work
, and strong culture of connection and global inclusion means that no matter your location, you’re part of a vibrant team with diverse experiences making a global impact each day. As we continue to revolutionize how the world interacts, we’re acquiring new skills and experiences that make work feel truly rewarding. Your career at Twilio is in your hands.
.
Hiring and how we work
We use Artificial Intelligence (AI) to help make our hiring process efficient. That said, every hiring decision is made by real Twilions!
Also, while we are a remote-first company, you may be asked to report in person on an ad-hoc basis for team gatherings, functional off-sites or customer meetings.
.
See yourself at Twilio
Join the team as Twilio’s next Technical Support Engineer 2.
About the job
This position is needed to support our customers’ use of Twilio’s Programmable Messaging product. This role will function as the voice of Twilio to our customers and partners and operate as a subject matter expert for Twilio’s Programmable Messaging API. In addition, focus on providing friendly, professional customer service, while problem-solving and demonstrating a high competency in communicating complex technical issues to both technical and non-technical audiences via phone, email, and chat mediums. Advanced time management skills are able to work well under pressure, and are proficient at developing workflows to remain efficient at tasks while still following standard processes and procedures.
Responsibilities
In this role, you’ll:
Work on support cases submitted by Wholesale providers.
Resolve complex customer requests
Assist customers with troubleshooting message deliverability issues and manage escalations with our Carrier partners.
Contribute to existing documentation including to correct errors, the elaboration of details, updates to current standards.
Speak with a customer on the phone in order to troubleshoot support issues or address questions.
Collaborate with your teammates and the Twilio Product and Engineering teams via Slack.
File Jira’s to report reproducible bugs and review our internal knowledge base to stay up to speed with industry shifts and standards.
Work with your manager to surface customer problems to assist in process betterment.
Qualifications
Twilio values diverse experiences from all kinds of industries, and we encourage everyone who meets the required qualifications to apply. If your career is just starting or hasn't followed a traditional path, don't let that stop you from considering Twilio. We are always looking for people who will bring something new to the table!
*Required:
Bachelor’s degree or equivalent work experience
3+ years of experience in a client-facing technical role, preferably in supporting REST API or enterprise software
Position requires flexibility in work schedule weekend, swing, and night shifts
Positive attitude and ability to communicate with a wide array of stakeholders
A firm understanding of the technology stacks common to the Web and telco ecosystem.
Functional knowledge of general-purpose programming languages.
Strong problem-solving and technical troubleshooting skills
Ability to professionally and diplomatically address customer concerns and provide concise feedback.
Ability to de-escalate tense/tough customer situations in a live environment.
Excellent reading comprehension, listening, and writing skills.
Desired:
Previous exposure or knowledge of Twilio products.
Coding experience in any language. (reading and debugging)
Previous experience with JIRA or a similar ticketing system.
Location
This role will be remote and based in India (Karnataka, Maharashtra, Tamil Nadu, Telangana, Delhi)
Travel
We prioritize connection and opportunities to build relationships with our customers and each other. For this role, you may be required to travel occasionally to participate in project or team in-person meetings.
What We Offer
Working at Twilio offers many benefits, including competitive pay, generous time off, ample parental and wellness leave, healthcare, a retirement savings program, and much more. Offerings vary by location.
Twilio thinks big. Do you?
We like to solve problems, take initiative, pitch in when needed, and are always up for trying new things. That's why we seek out colleagues who embody our values — something we call
Twilio Magic
. Additionally, we empower employees to build
positive change in their communities
by supporting their volunteering and donation efforts.
So, if you're ready to unleash your full potential, do your best work, and be the best version of yourself, apply now! If this role isn't what you're looking for,
please consider other open positions.
.
Stay alert to recruitment fraud
We care about your safety. Scammers sometimes impersonate Twilio recruiters through fake job postings, emails, websites, or messages. Please ensure you are engaging with an official @
twilio.com
email address. We will never ask for payment, gift cards, cryptocurrency, or banking information during the recruiting process. We do not make job offers without a formal interview process or conduct interviews exclusively through text-based messaging apps.
.
Twilio is proud to be an equal opportunity employer.
We do not discriminate based upon race, religion, color, national origin, sex (including pregnancy, childbirth, reproductive health decisions, or related medical conditions), sexual orientation, gender identity, gender expression, age, status as a protected veteran, status as an individual with a disability, genetic information, political views or activity, or other applicable legally protected characteristics. We also consider qualified applicants with criminal histories, consistent with applicable federal, state and local law. Qualified applicants with arrest or conviction records will be considered for employment in accordance with the Los Angeles County Fair Chance Ordinance for Employers and the California Fair Chance Act. Additionally, Twilio participates in the E-Verify program in certain locations, as required by law.
ML / DS Engineer (Classic ML) IT Вакансии Мы ищем опытного ML/DS инженера для разработки и внедрения моделей классического машинного обучения, решения бизнес-задач и построения ML-пайплайнов.
Location: Москва
Готовим данные для GigaChat и GigaChat Vision — от pretrain с нуля до alignment. Собрали корпус на 15 триллионов токенов. Открыли [GigaChat 3.1 (702B)](https://huggingface.co/ai-sage/GigaChat3.1-702B-A36B) и [GigaChat 3.5 (432B)](https://huggingface.co/ai-sage/GigaChat3.5-432B-A28B). Опубликовали [статью на ACL](https://aclanthology.org/2025.acl-demo.10/); ещё две статьи проходят ревью на A\*-конференциях.
У нас — сильная исследовательская команда, сложные задачи в LLM и мультимодальности и ресурсы для проверки новых идей.
Чтобы познакомиться с работой команды
Наши доклады:
[Данные и инфраструктура GigaChat — HighLoad++ 2025](https://highload.ru/moscow/2025/abstracts/16850)
[Качество данных и эксперименты — AiConf 2025](https://aiconf.ru/2025/abstracts/15853)
[Синтетические задачи по программированию — AiConf 2026](https://aiconf.ru/2026/abstracts/17916)
Как это делают другие команды: [NVIDIA Nemotron-CC](https://research.nvidia.com/labs/adlr/Nemotron-CC/) · [Hugging Face SmolLM3](https://huggingface.co/blog/smollm3)
Обязанности
* Улучшать pretrain-данные: обучать модели оценки качества, кластеризовать корпуса, подбирать смеси и измерять их влияние на качество модели.
* Создавать alignment-данные для SFT и RL в разных доменах: инструкции, предпочтения и агентные траектории; разрабатывать среды, задачи и проверки для обучения работе с инструментами.
* Генерировать синтетику для математики, кода и reasoning; проверять решения исполнением кода и моделями-судьями.
* Исследовать density sampling, способы токенизации с упаковкой последовательностей, включая best-fit packing; проверять гипотезы в ablation-экспериментах.
* Готовить датасеты для мультимодального обучения, включая interleaved-данные с чередованием текста и изображений.
* Масштабировать обработку сотен миллиардов веб-документов и OCR миллиардов PDF; ускорять распределённые пайплайны и генерацию на GPU.
Требования
* Уверенный Python, алгоритмы и структуры данных; основы ML, линейной алгебры и вероятности.
* Практику с PyTorch, NLP/CV или данными — учебные и личные проекты подходят.
* Linux и Git, чтение статей на английском, умение проверять гипотезы и доводить задачи до результата.
* Активное использование AI-агентов в работе.
**Будет плюсом**
* LLM/VLM, vLLM/SGLang, Spark/YTsaurus, C++/Rust;
* исследовательские проекты,
* ML-соревнования или олимпиадное программирование.
Условия
* MacBook M4 (с VPN), корпоративные подписки на AI-агентов.
* 50 тысяч CPU и большое количество GPU для обработки данных, обучения и синтетики.
* После успешной стажировки — переход в штат команды.
Location: Brazil; Portugal
SUMMARY:
As a Data / ML Engineer, you’ll combine hands-on data analysis, data engineering and applied data science to build and improve production ML solutions. You’ll work closely with Product Owners to understand what they want to learn or improve, explore the data and propose experiments. You’ll also collaborate with Data Scientists and Engineers to build and maintain the pipelines that support these solutions in production.
WHAT WILL YOU BE DOING:
Analyse data to answer product questions. Explore datasets, identify trends and anomalies, and communicate findings that help Product Owners make decisions.
Work with Product Owners to shape experiments. Clarify requirements, translate product questions into testable hypotheses, suggest experiments and help define how to measure success and interpret results.
Build and maintain end-to-end ML pipelines. Cover ETL, feature engineering, model training, deployment, batch scoring, API-based inference and monitoring.
Work with our data and ML stack. Use AWS SageMaker, AWS Glue, AWS Lambda, MLflow, Spark and Airflow, with Great Expectations for data quality where appropriate.
Collaborate with Data Scientists and Engineers. Improve how models are developed, deployed and operated in production. Work in an Agile Scrum environment and apply practices such as TDD and DDD where appropriate.
WHAT WE ARE LOOKING FOR:
Hands-on experience across data engineering and applied data science, with the ability to move between exploratory analysis, experimentation and production pipeline development.
Strong data analysis skills, including the ability to investigate datasets, interpret findings and explain what they mean for product decisions.
Experience working directly with Product Owners to understand requirements, propose experiments and define success metrics.
Strong experience building end-to-end production ML pipelines, covering ETL, feature engineering, model training, deployment, serving and monitoring.
Proficiency with AWS SageMaker, AWS Glue and AWS Lambda, plus hands-on experience with MLflow, Spark and Airflow.
Clear communication and effective collaboration with Product Owners, Data Scientists and Engineers.
AWESOME BUT NOT REQUIRED:
Experience with Google Vertex AI.
Familiarity with the Great Expectations Framework for data quality.
Proven experience working in Agile Scrum environments and practising TDD and DDD.
WHAT’S IN IT FOR YOU?
Be part of our collegial environment where responsibility and authority are shared equally amongst colleagues and help create our company culture
A culture in which we don’t criticise failure but ensure we learn from our mistakes
An Agile environment where your ideas are welcome
The possibility to grow and experience different projects
Ongoing Training & Mentoring
The possibility to travel
- ATTENTION! THIS POSITION IS FOR PORTUGAL OR BRAZIL BASED ONLY
Сегодня мы расширяем команду и ищем Инженера данных для работы над внешними проектами в таких сферах, как ритейл, EdTech, банкинг и других. Чем предстоит заниматься Проектировать и разрабатывать потоки данных на ETL/ELT-инструментах;
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