Location: United States
What The Role Is
As a
Senior Engineer
at Babylist, you take on hard problems and own them end-to-end. Millions of families depend on what we build. Agents write most of the code now. So the hard part is yours: what to build, how it should work and whether what shipped was right. You're still in the code for the genuinely hard problems. Agents handle the volume. You spend your time on the parts that need a person.
We're building well beyond the registry now: the financial side of raising a kid, maternal health made simpler and more human, the education new parents are looking for and the community around them. The hard problems run across all of it, plus the platform underneath and the AI we already ship to families. You'll start on a team, but you won't be boxed into it. The roadmap is open, your scope grows as you do and you have a say in what you take on next. Senior here means owning whole problems; Staff is the next step up, setting direction across a domain.
What You'll Own
A Senior Engineer here owns problems, not just features. You're handed an outcome, you decide what to build, ship it and own whether it worked. You act on incomplete information and change course fast when the evidence says you were wrong.
What you do depends on what the team needs:
Frame the problem with your PM as a peer, run the experiment and bring customer evidence into what gets built.
Harden a critical path, kill a class of incidents or design the abstraction your team builds on.
Be the reviewer people want on the risky changes.
Manage up with crisp choices: raise the risks early and protect the right tradeoffs.
Share what you're learning about AI openly, so the whole team gets sharper.
A few problems people at this level are working on right now:
Deciding what the registry recommends to each family, from the ranking to the model behind it, and proving in a live experiment that it actually helps.
Building the evals system that catches our AI support agent making things up before a customer does.
Making a child's info one source of truth instead of five disconnected flows, so parents set it up once and new products like Early Investor build on it.
Who You Are
You've been shipping production systems for years, and you've got the judgment to show for it. You can pick up an ambiguous problem and start moving before anyone hands you the full picture.
The strongest Senior engineers here are generalists, and usually the most prolific builders on their team. You go wherever the problem leads: a backend service one week, a stubborn frontend bug the next, the data pipeline after that. When it's hard you dig in, and you learn unfamiliar parts of the stack fast. Range is the Senior signature.
Compensation
We post real numbers. For a US-based Senior Engineer, the starting base salary range is $202,200 to $251,700, plus a target annual bonus of 15 percent of base. That's total target cash of roughly $232,530 to $289,455. On top of that you get meaningful equity and a 401(k) match. Where you start in that range depends on your experience, and your pay grows from there with performance and scope.
How We Build
AI is the default here. Engineers run agentic sessions for most of the work, and a lot of the interesting engineering now lives in the scaffolding that makes the agents good: the eval harnesses, the curated context, custom review skills and fast CI. Agents also triage incidents and handle a big share of support. A human always owns the outcome. The architecture is intentionally simple: one Rails monolith, MySQL and few moving parts. That's deliberate. Simple infrastructure lets us move fast and lets AI reason about the whole system, so the hardest problems are the ones in front of customers.
The Stack
Core app:
Rails, Packwerk, React, TypeScript, Sidekiq
Mobile:
iOS (Swift), Android (Kotlin)
Data, search & events:
MySQL, Snowflake, dbt, Airflow, Weaviate, WarpStream, Hex, Sigma
Machine learning:
deep learning, matrix factorization, retrieval & ranking, AWS SageMaker, MLflow
AI & dev tooling:
Claude Code, Devin, Linear, CodeRabbit, Warden, LangChain, Bedrock AgentCore, Maxim
Infra & ops:
AWS, Kubernetes, Terraform, GitHub Actions, Datadog, incident.io, LaunchDarkly
Key integrations:
Shopify (payments), Iterable (CRM)
Why Babylist
An engineer, expecting her first baby, couldn't find the registry she wanted. So she built it. That's how Babylist started, and it's still how we work: engineers solving problems for families. Becoming a parent is one of the biggest moments in a person's life. Millions reach it for the first time every year, making thousands of decisions and figuring it out as they go. That's who we build for, and we're a long way from done.
Ten million people give gifts through Babylist every year. We did more than $750M in revenue in 2025, up 45 percent over the year before, and we've been profitable for eight years while staying independent. So you can take on a hard, multi-year problem without watching over your shoulder for the next round or the next correction. And the team is small, around 65 engineers, so what you ship stays visible and your scope stays wide.
How We Work
Remote-first across the US and Canada, and we have been for years. That's not changing. We trust you to own your time and your outcomes, and we get everyone in a room together twice a year. Teams are small, pods of three to five engineers, so nothing you ship disappears into a committee. You'll work shoulder to shoulder with product, design and data, and with the partners across the business who rely on what you ship. You'll also stay close to customers yourself: sitting in on user interviews, watching session recordings, riding along with support. Here that's part of the engineering job, on a regular basis.
How We Hire
Three rounds, usually two to three weeks, start to finish.
Recruiter conversation (30 minutes).
Trade context: what you want next, what we're building and straight answers on comp, team and remote.
Technical screen (1 hour).
One round, no AI, language-agnostic. Reach for Google when you normally would. We just want to see how you reason from first principles.
Final round (4 hours).
Four one-hour interviews: system design, AI-assisted coding with the tools you'd actually use here, product sense and culture and values. You'll hear back either way within 24 to 48 hours.
If your timeline is tight, tell us and we'll move faster.
Benefits
Company-paid medical and fully covered dental and vision
A 401(k) match
Generous paid parental leave for birthing and non-birthing parents, plus a gradual return-to-work program
Winter Wonder Week, a paid company-wide week off at the end of the year
A remote-work stipend
Mental-health and wellness support
A Few Things To Know
We record and transcribe interviews to evaluate candidates, in line with applicable privacy laws.
We expect you to use AI in your work and we welcome it in the process, but what you submit and say should reflect your own thinking.
If you have a family member or close relationship with a Babylist employee, let your recruiter know.
Official outreach only ever comes from an @babylist.com address.
Задачи:
— Улучшать стабильность и качество текущих AutoML алгоритмов, оптимизировать код;
— Разрабатывать новые сценарии платформы для аналитиков (поиск аномалий, очистка данных, кластеризация, анализ дрейфа данных/концепта);
— Улучшать отчетность и артефакты по полученной модели (отчёт по модели с интерпретацией LLM, графики, таблицы);
— Обновлять документацию и технические инструкции по сценариям платформы;
— Взаимодействовать по внедрению новых сценариев и фич платформы с MLOps командой;
— Проводить анализ потребностей аналитиков, формализовать их в сценарии;
— Поддерживать пользователей (аналитиков);
— Отвечать за релизный цикл библиотеки;
— Проводить ревью PR от других DS.
Требования:
— Опыт в Data Science от 3 до 5 лет (важна насмотренность к кейсам и разным моделям, опыт промышленной разработки);
— Уверенное владение ML- и DL-стеком Python: PyTorch, LightGBM / XGBoost / CatBoost, Scikit-Learn, Pandas, NumPy;
— Умение работать с инструментами: Spark, Hadoop, Hive, MLflow, Airflow / Argo Workflows;
— Обязателен опыт в табличных данных и классическом ML (градиентный бустинг, логистическая регрессия, кластеризация);
— Будет большим плюсом: Контрибьют в ML-библиотеки; Опыт full-stack разработки;
— Не подходят кандидаты с чистой карьерой в CV / NLP / LLM без серьёзного бэкграунда в таблицах.
Условия:
— Работа в аккредитованной IT компании;
— Формат работы: удалённый по РФ (или гибрид — на выбор);
— Расширенный ДМС (со стоматологией);
— Выдача необходимой для работы техники (ноутбук);
— Возможность воспользоваться реферальной программой: «Приведи товарища»;
— Участие в Бонусной программе;
— Помощь с ипотекой и другими пособиями;
— Возможность построить карьеру в рамках ведущих компаний России.
Location: San Francisco, CA, USA
About the Role
The Data engineering team has been created keeping in mind the importance and criticality of data for the overall success of Chime. The mission of this group is to build scalable data artifacts and insights that enable accurate, governed, data-driven decision-making.. As a core member of the team, you will have the opportunity to build scalable data pipelines and frameworks. Additionally, you will have the unique opportunity to architect and build workflows that could potentially become de facto standards for the fintech industry.
In this role, you can expect to
Be a hands-on data engineer, building, scaling and optimizing ETL pipelines
Design data schemas and scale them data for 10x data growth
Ownership of all aspects of data - data quality, data governance, schema design, data quality and security
Develop scalable data architecture and standardized data models that enable self-serve data insights using AI.
Own the ETL workflows and make sure the pipeline meets data quality and availability requirements
Work closely with partner teams, like Data Science, Analytics and DevOps
To thrive in this role, you have
5+ years experience transforming data to governed and lucid datasets
5+ years of hands-on experience to build and deploy production-quality data pipelines
5+ years of experience working with stakeholders to provide business insights
5+ years of experience writing SQL, Spark, AWS Glue, EMR, Airflow, Python
3+ years of hands-on experience using any MPP database system like Snowflake, AWS Redshift or Teradata
Track record of successful partnerships with Analytics, Data Science and DevOps teams
Understanding of key metrics for data pipelines and has built solutions to provide visibility to partner teams
Engineers are required to participate in on-call rotation. Being on call may include responding to incidents outside of regular working hours when necessary.
#LI-Onsite #LI-WW1
Below is the base salary offered for this role and level of experience. Full-time employees may also be eligible for bonus(es), competitive equity, and benefits. For commissioned roles, the base salary listed in this job description does not include incentive/variable pay. The actual base salary offered may be higher, depending on your location, skills, qualifications, and experience.
Wage Notice
$164,000
—
$227,000 USD
A little about us
At Chime, we believe that everyone can achieve financial progress. We created Chime—a financial technology company, not a bank*—on the premise that core banking services should be helpful, easy, and free. Through our user-friendly tools and intuitive platforms, we empower our members to take control of their finances and work towards their goals. Whether it's starting a savings account, purchasing a first car or home, launching a business, or pursuing higher education, we're proud to have helped millions unlock their financial potential.
We're a team of problem solvers, dreamers, and builders with one shared obsession: our members. From day one, Chimers have worked tirelessly to out-hustle and out-execute competitors to bring our mission to life. Their grit and determination inspire us to work harder every day to deliver the very best experience possible. We each bring an owner's mindset to our work, refusing to be outdone and holding ourselves accountable to meet and exceed the highest bars for our teams, our company, and our members.
We believe in being bold, dreaming big, and taking risks, while also working together, embracing our diverse perspectives, and giving each other honest feedback. Our culture remains deeply entrepreneurial, encouraging every Chimer to see themselves as stewards of our mission to help everyday Americans unlock their financial progress.
We know that to achieve our mission, we must earn and keep people's trust—so we hold ourselves to the highest standards of integrity in everything we do. These aren't just words on a wall—our values are embedded in every aspect of our business, serving as a north star that guides us as we work to help millions achieve their financial potential.
Because if we don't—who will?
*Chime is a financial technology company, not a bank. Banking services provided by The Bancorp Bank, N.A. or Stride Bank, N.A., Members FDIC.
What we offer for our full-time, regular employees
🏢 Our in-office work policy is designed to keep you connected - with four days a week in the office and Fridays from home for those near one of our offices, plus team and company-wide events depending on location.
💻 Benefits that support your work and life, including backup child, elder, and pet care and subsidized commuter benefits for eligible employees.
✨ Comprehensive health, financial, and wellbeing benefits designed to support you at every stage of life.
🏝 Generous vacation policy and company-wide paid days off
🫂 1% of your time off to support local community organizations of your choice
👟 Annual wellness stipend to use towards eligible wellness related expenses
👶 Up to 22 weeks of paid parental leave for birthing parents and 12 weeks of paid parental leave for non-birthing parents
👪 Access to family planning reimbursement
💚 A challenging and fulfilling opportunity to join one of the most experienced teams in FinTech and help millions unlock financial progress
We know that great work can’t be done without a diverse team and inclusive environment. That’s why we specifically look for individuals of varying strengths, skills, backgrounds, and ideas to join our team. We believe this gives us a competitive advantage to better serve our members and helps us all grow as Chimers and individuals.
Chime is proud to be an Equal Opportunity Employer. We consider qualified applicants without regard to race, color, ancestry, religion, sex, national origin, sexual orientation, gender identity, age, marital or family status, disability, genetic information, veteran status, or any other legally protected basis under provincial, federal, state, and local laws, regulations, or ordinances. We will also consider qualified applicants with criminal histories in a manner consistent with the requirements of state and local laws, including the San Francisco Fair Chance Ordinance, Cook County Ordinance, NYC Fair Chance Act, and the LA City Fair Chance Ordinance, and consistent with Canadian provincial and federal laws. If you have a disability or special need that requires accommodation during any stage of the application process, please contact:
accommodations@chime.com
.
To learn more about how Chime collects and uses your personal information during the application process, please see the
Chime Applicant Privacy Notice
.
Location: Warsaw, Poland; Madrid, Spain; Tbilisi, Georgia; Yerevan, Armenia; Bratislava, Slovakia; Podgorica, Montenegro
CloudLinux is transforming the Linux infrastructure market by ensuring security and stability for over 500,000 servers worldwide. Our products - CloudLinux OS and Imunify360 - are the de facto standard in the hosting industry and Enterprise segment.
We are seeking a visionary engineer to lead the evolution of our data platform. In 2025, we are shifting from classic database administration to an Internal Database-as-a-Service (DBaaS) model. We need a specialist who doesn’t just "configure backups," but designs resilient distributed systems, writes code to automate infrastructure, and transforms databases into a reliable service for product teams.
If you are tired of endless tickets and want to build platforms capable of processing petabytes of data, this role is for you.
Your Challenges & Responsibilities:
DBaaS Architecture:
Design and implement a self-service platform based on
Terraform
and
Ansible
, enabling the deployment of HA clusters (PostgreSQL and ClickHouse, MongoDB, Redis) in a heterogeneous environment (Bare Metal + OpenNebula + Kubernetes + Public Clouds). You will turn infrastructure into a product.
Scaling ClickHouse:
Manage exponentially growing analytics clusters (12+ clusters, tens of terabytes of data). You will tackle sharding, table engine optimization (ReplicatedMergeTree), and building reliable S3 backup pipelines under high load.
Data Platform & Analytics Support:
Maintain and scale the infrastructure for Apache Airflow and Redash. You will ensure the reliability of ETL pipelines and visualization tools, bridging the gap between raw infrastructure and the data analytics team.
Reliability as Code:
Implement SRE practices in data management. Replace manual incident response with automated self-healing mechanisms. Define and implement SLO/SLI for all databases.
Stack Modernization:
Lead the migration process from legacy solutions to modern cloud patterns. Participate in decision-making regarding the implementation of Kubernetes operators for stateful workloads.
Expertise & Mentorship:
Serve as the technical authority for product teams, helping them optimize data schemas and SQL queries for high-load systems.
Our Tech Stack:
Databases
: PostgreSQL 15+ (Patroni, PgBouncer), ClickHouse (Sharded/Replicated), MongoDB, Redis, Kafka
Data & Analytics:
Apache Airflow, Redash (Infrastructure & Integration).
Infrastructure:
Own 3+DC colocation (OpenNebula, Kubernetes, Bare Metal), AWS, Google Cloud, Azure, DO – Hybrid Cloud.
Automation & IaC:
Terraform, Ansible, Python/Go, GitLab, Jenkins, Gerrit.
Observability
: VictoriaMetrics, Grafana, Loki.
Why CloudLinux?
Culture:
A Remote-first company with an "Employees First" principle. We value results, not hours in the office.
Impact:
Your architectural decisions will determine the stability of services used by thousands of companies around the world.
Growth:
We support professional development and pay for training and conferences.
Requirements
What We Expect From You:
AI-Augmented Engineering:
You don't view AI as a replacement for deep technical fundamentals, but as a high-leverage tool. We actively use AI agents (Claude, Codex, Gemini, etc.) to automate boilerplate, analyze complex logs, and speed up research. We expect you to be open to modern workflows and integrate AI into your day-to-day operations, allowing you to focus your brainpower on the true architectural challenges.
Deep PostgreSQL Expertise (5+ years):
You know MVCC internals, understand locking mechanics, can configure Patroni and PgBouncer "with your eyes closed," and have experience with seamless major version upgrades under load.
ClickHouse Mastery:
Experience operating large clusters, understanding ZooKeeper/ClickHouse Keeper, sharding, replication internals, and the ability to diagnose performance issues at the data-part level.
Engineering Mindset (SRE/DevOps):
You hate doing the same task twice by hand. Experience writing complex Terraform modules and Ansible roles is mandatory. Programming skills in
Python
or
Go
for automation are a huge plus.
Hybrid Environment Experience:
You understand the differences between running DBs on Bare Metal vs. Kubernetes vs. Cloud and know how to optimize TCO and disk subsystem performance (NVMe, Network Storage).
Systems Approach:
You see the big picture - from the network packet to the application business logic. You understand the importance of security (FIPS, Audit logs) and Disaster Recovery.
English:
upper-intermediate or higher - to ensure clear communication of progress within the teams
Nice to Have:
Experience building an Internal Developer Platform (IDP).
Experience operating databases in Kubernetes (CloudNativePG, Altinity Operator).
Experience working in Cloud and Hosting providers on similar services.
Benefits
What's in it for you?
A focus on professional development.
Interesting and challenging projects.
Fully remote work with flexible working hours, which allows you to schedule your day and work from any location worldwide.
Paid 24 days of vacation per year, 10 days of national holidays, and unlimited sick leaves.
Compensation for private medical insurance.
Co-working and gym/sports reimbursement.
Budget for education.
The opportunity to receive a reward for the most innovative idea that the company can patent.
By applying for this position, you consent to the processing of your personal data as described in our Privacy Policy (
https://cloudlinux.com/candidate-privacy-notice
), which provides detailed information on how we maintain and handle your data.
Location: Morocco
We are looking to hire passionate Senior AI Engineers to help turn data into intelligent, production-ready solutions. You will work across the full AI stack: traditional machine-learning models, large language models (LLMs), computer-vision pipelines, and analytics / forecasting workflows. If you enjoy exploring data, building state-of-the-art models, and shipping reliable AI services, we would love to meet you.
Responsibilities
Model Development – Design, train, fine-tune, and evaluate models spanning classical ML, deep learning (CNNs, transformers), and generative AI (LLMs, diffusion).
Data Exploration & Analytics – Conduct exploratory data analysis, statistical testing, and time-series / forecasting to inform features, prompts, and business KPIs.
End-to-End Pipelines – Build reproducible workflows for data ingestion, feature engineering / prompt stores, training, CI/CD, and automated monitoring.
LLM & Agentic AI Engineering – Craft prompts, retrieval-augmented generation (RAG) pipelines, and autonomous/assistive agents; fine-tune LLMs on domain-specific datasets to boost accuracy and align outputs with product requirements.
AI Automation & Integration – Expose AI components as micro-services and event-driven workflows; integrate with orchestration tools (Airflow, Prefect) and business APIs to automate decision pipelines.
Continuous Learning – Track advances in LLMs, vision, and analytics; share insights and best practices with the wider engineering team.
Mentor junior engineers and contribute to technical direction and engineering best practices.
Requirements
BSc in Computer Science, Mathematics, or related field.
5+ years of professional experience working on AI/ML projects.
Good command of English and Arabic (written and spoken).
Proficient in Python and core libraries (PyTorch / TensorFlow, scikit-learn, pandas, NumPy).
Solid understanding of machine-learning algorithms, deep-learning fundamentals, and basic statistics.
Experience with data wrangling and visualization (Matplotlib / Plotly) and exploratory analysis.
Familiarity with at least one of: OpenCV, Hugging Face Transformers, LangChain, MLflow, or similar.
Good grasp of software-engineering best practices: Git, code reviews, testing, CI.
Preferred Qualifications
Knowledge of C++ or C# for performance-critical modules.
Experience deploying models via Docker, Kubernetes, or cloud AI services.
Exposure to vector databases and RAG workflows.
Skill in BI / dashboard tools (Power BI, Tableau, Streamlit) or time-series frameworks (Prophet, statsmodels).
Familiarity with MLOps / LLMOps tooling (DVC, MLflow Tracking, Weights & Biases, BentoML).
Experience with image processing techniques (e.g., OpenCV, image segmentation, feature extraction)
Experience with Spark (PySpark) and distributed data processing, including usage of platforms such as Databricks, AWS EMR, or GCP Dataproc.
Strong SQL skills and experience working with large-scale datasets, including partitioning and performance tuning.
Familiarity with modern data lake architectures and scalable data storage concepts.
Location: Yerevan; Poland; Ukraine; Serbia; Valencia
Workplace: remote
About Provectus
Provectus is an AWS Premier Partner and an Anthropic Strategic Partner, working at the frontier of applied AI. We help enterprises turn Claude, agentic systems, and their own data into measurable business outcomes — through bespoke applications, managed services, and advisory engagements. With offices in North America, LATAM, and EMEA, we partner with clients worldwide.
Our work centers on two verticals — Financial Services & Insurance and Healthcare & Life Sciences — where we deploy five pre-built AI Blueprints: Submission Flow, Portfolio Lens, Asset Flow, Revenue Flow, and Evidence Lens. Each Blueprint rebuilds a critical business process front to back, shipped from working code and tuned to a client's specific book, regulators, and operating posture.
Our team holds 100+ AWS certifications, is Claude Code certified, and co-delivers Anthropic's Agentic SDLC program, Cowork Activation, and AI Blueprint engagements.
Where this role sits
You will work in a small, senior pod alongside an FDX; our delivery arc is Sprint → Enable → Realize:
Forward Deployed Executive (FDX)
owns the commercial relationship and the business outcome. Works alongside the client's leadership or C-suite level to move the client's KPIs — revenue growth, cost reduction, risk reduction.
Forward Deployed Engineer (FDE)
embeds with a client to change how that client operates. You own the method; nobody hands you a ticket. You map the client workflow as it actually happens, identify the business problem underneath it, build a working AI solution, present to the client in the language of outcomes, and transfer it. Provectus maintains industry Blueprints — working systems that have already shipped for a client in the same industry — so you begin from running code and tuning it to this client's specific book, regulators, and operating posture. You will be measured on whether the Business Unit's number moved, not on hours or scope delivered.
Requirements:
Mindset
Proactive and self-directed; identify problems before they're handed to you
Comfort with ambiguity and ownership. Engagements start underspecified by design. Closing that gap is the job
B2+ English, comfortable collaborating across distributed, multicultural teams
Client Engagement
You are willing to spend time understanding and doing someone else’s job on the client's side before you write a line of code
Credible with senior stakeholders — you can hold a redesign conversation with a BU head and a scoping conversation with a CTO, presenting outcomes to them
You can produce a scoped, phased delivery plan with clear deliverables, dependencies, and risks — and estimate what it will cost to build and to run
Technical depth
7+ years building and running production systems.
Solid AI/ML foundations. You understand what the models do well enough to reason about failure modes
Designed and shipped to production LLM applications and agentic workflows — not demos, not POCs, not notebooks
Agentic orchestration: multi-step workflows, graph-based orchestration, tool use, state management, and recovery from partial failure
Experience with LLM APIs (Anthropic, AWS Bedrock, or OpenAI) and agent frameworks.
Experience building and optimizing RAG systems in production
Strong engineering fundamentals — dropped into an unfamiliar codebase or language, you’re productive. Python and/or TypeScript proficiency; depth matters more than stack.
Experience in making and defending architectural trade-off decisions
Hands-on AWS production depth: Bedrock, Bedrock AgentCore, Lambda, ECS, S3, SQS, ECR, or similar. GCP or Azure is a plus
Cloud-native delivery: containers, ECS or Kubernetes, IaC, and CI/CD applied to AI pipelines
You evaluate. You have built or owned an eval suite for a non-deterministic system, and you can explain what you measured, how you produced ground truth, and what gated a release
Model and agent monitoring, drift detection
Cost and latency discipline: model tiering, caching, and the ability to say what a workload costs to run before it runs
Hands-on production experience with the Claude ecosystem — Claude Code, CLAUDE.md, hooks, skills files. Spec-driven development — writing the intent, constraints, and acceptance criteria before you let an agent build — is a strong plus
MCP: you can say why an agent would prefer it to a REST integration. Having authored a server is a plus
What you’ll do:
Take the seat
Sit with the client and the Forward Deployed Executive at the start of an engagement. Learn the function from inside, not from a requirements doc, and redesign the function from first principles.
Reach working fluency in a new domain — insurance underwriting, healthcare revenue cycle, asset flow.
Build
Design and ship production GenAI systems into the customer’s environment (cloud-native data, LLM-based, and agentic AI solutions). Implement and optimize RAG systems for production use cases
Build the evaluation harness before you build the feature. Define what working means, instrument it, and let the evals drive the design.
Write production code across the stack — AI, backend services, data pipelines. We choose tools to fit the customer.
Take systems to production on AWS (GCP or Azure where the customer requires it): containerised, CI/CD, automated testing, monitoring, and maintainable after we leave. Hand the system over to the client.
Start from the blueprint, and feed the blueprint. What you learn in the field becomes the baseline the next engagement starts from.
Lead architecture reviews, produce technical design documents, and contribute to standards. Mentor engineers and share knowledge across the team.
Own the outcome.
Work in a pair with a FDX who carries the Business Unit’s KPIs. Your work is measured against the same number.
Own the technical direction of technical proposals and scoping. Drive adoption. Change management is part of the engineering job here.
Be credible with the customer’s engineers and their executives.
Shape what we commit to before we commit to it.
Nice to Have:
Prior experience as a founder, CTO, or engineering leader who has chosen to return to individual contribution
Experience in one of the industries: financial services, insurance, healthcare
Consulting, professional services, or other embedded customer-facing delivery
A2A: you can explain agent-to-agent interoperability
AWS and Claude Code Certifications
CI/CD pipeline experience (GitHub Actions, GitLab CI)
Experience in an additional language (Go, TypeScript, or Rust)
Experience with Apache Spark, Apache Airflow, Kafkа
What We Offer:
The chance to shape how leading enterprises across LATAM, Europe, and North America adopt AI, from strategy through first deployment
A forward-deployed model working in small, senior teams alongside Principal Architects and Forward Deployed Engineers
A growing AI delivery practice where you help build the tooling and frameworks, not just use them
Remote-friendly culture
Internal training programs with full support for Claude, AWS, and other professional certifications, conference attendance
Career growth; we actively develop our engineers
Access to the latest AI tools and premium subscriptions
Long-term B2B collaboration
Private medical insurance or a budget for your medical needs
Paid sick leave, vacation, and public holidays
Equipment and all the tech you need for comfortable, productive work
How we hire:
Intro conversation. The role, your background and aspirations, tech questions.
Technical interview with live engineering sessions. Real problems, your own editor, you may use an LLM assistant
HR Interview. Soft skills and expectations
HM interview. Tech questions; a live engineering session is also possible
Location: ES - Barcelona, Spain; ES - Spain
Scopely is looking for an
Analytics Engineer, Finance
to join our
Finance team
in
Barcelona, Spain
, on a hybrid basis,
working 3 days a week from our hub.
At Scopely, we care deeply about what we do and want to inspire play, every day - whether in our work environments alongside our talented colleagues, or through our deep connections with our communities of players. We are a global team of game lovers who are developing, publishing and innovating the mobile games industry, connecting millions of people around the world daily.
Show us the money! As the Finance team, we’re number crunchers with top-notch analytical and reporting skills. As a shared service, we get to work with all of Scopely's talented studios.
In this role, you will help to improve the reliability, accuracy, and maintainability of Finance data workflows by developing and supporting automated pipelines, data transformations, and reporting models. Working closely with stakeholders and the Lead Analytics Engineer in Finance, this role contributes to reducing manual processes, strengthening data quality, and ensuring dependable financial information for monthly close, revenue reporting, and accounting activities.
What You Will Do:
Partner with Finance stakeholders to understand business requirements, financial processes, and controls, translating them into practical technical solutions with guidance from the Lead Analytics Engineer.
Develop, maintain, and troubleshoot data pipelines, SQL transformations, and reporting models supporting monthly close, revenue reporting, and accounting workflows.
Investigate missing, delayed, inconsistent, or incorrect financial data, identify root causes, and implement reliable solutions.
Help modernize legacy SQL, scheduled workflows, and manual processes into maintainable, documented, and dependency-aware pipelines using dbt.
Build and improve automated data-quality checks, reconciliations, monitoring, and alerting to strengthen the reliability of Finance data workflows.
Apply Git, code review, testing, and deployment practices to improve the quality and maintainability of Finance data assets.
Support the automation of recurring spreadsheet-based processes and manual handoffs, while maintaining technical documentation, dependency maps, runbooks, and recovery procedures.
Collaborate with the Lead Analytics Engineer to apply engineering standards and contribute to governed, reusable models within the Looker semantic and reporting layer.
What We're Looking For:
Strong SQL skills and experience developing and maintaining production data transformations.
Experience working with a modern cloud data warehouse such as BigQuery, Snowflake, or Redshift.
Experience with data transformation frameworks such as dbt, Dataform, or equivalent technologies.
Knowledge of Git, version control, code reviews, and collaborative software development practices.
Familiarity with data-quality checks, automated testing, monitoring, or reconciliation processes.
Strong debugging and problem-solving skills, including the ability to investigate issues in inherited or imperfectly documented systems.
Experience working with Finance, Accounting, Revenue Accounting, month-end close, or audit-related data.
Ability to communicate technical concepts clearly to non-technical stakeholders, collaborate with engineering colleagues, and independently progress defined technical problems while seeking guidance when appropriate.
Openness to learning and responsibly using AI-supported tools to improve SQL development, documentation, debugging, testing, and workflow efficiency, while maintaining appropriate data security and validation practices.
Bonus Points:
Familiarity with financial controls, reconciliation, general-ledger concepts, or revenue recognition.
Experience in gaming, digital products, app-store revenue, or virtual economies.
Experience with data lineage, CI/CD, observability, or data governance practices.
Experience working with GCP, Airflow, Cloud Composer, or Looker.
Experience modernizing legacy SQL pipelines or stored-procedure-heavy environments.
Familiarity with orchestration tools for scheduling, dependency management, monitoring, and recovery.
Experience supporting business-critical workflows with defined service-level agreements (SLAs).
Working knowledge of Python or another programming language used for automation and data workflows.
Experience using or integrating agentic workflows in Finance processes.
Please ensure that the résumé/CV you attach is written in English.
At Scopely, we create games for everyone - and want to ensure that the people behind our games reflect that! We are committed to creating a diverse, supportive work environment where everyone is treated with respect. We are committed to providing equal employment opportunities and welcome individuals from all backgrounds to join us & embrace the adventure!
About Scopely
Scopely is a leading video game and global interactive entertainment company, home to many of the world’s most beloved and enduring experiences, including two of the most successful mobile games of all-time “MONOPOLY GO!” and “Pokémon GO,” along with “Stumble Guys,” “Star Trek™ Fleet Command,” “MARVEL Strike Force,” “WWE Champions,” the Scrabble® franchise, “Yahtzee® With Buddies,” and many others. Across mobile, web, PC, and console, Scopely creates, develops, publishes, and live-operates one of the most diversified and award-winning portfolios in the games industry — bringing hundreds of millions of players together through a shared love of play.
Founded in 2011, Scopely is powered by its exceptional team — including thousands of world-class gamemakers around the globe, a distinctive tenet-driven culture, and its proprietary technology platform, Playgami. Together, these strengths have fueled Scopely’s position as the #1 mobile games company in the U.S. and #2 globally, generating more than $10 billion in lifetime revenue. Whether building global sensations like “MONOPOLY GO!” from the ground up, or expanding through strategic acquisitions, including the FoxNext, GSN, and Scopely Explore games businesses — Scopely consistently delivers experiences players love today and return to for years to come.
Recognized multiple times as one of the "100 Most Influential Companies in the World" by TIME magazine and one of Fast Company's "World's Most Innovative Companies" and “Best Workplaces for Innovators,” Scopely believes that video games can be a force for good — creating meaningful connections, vibrant communities, and making life better through play.
Scopely has global operations and partners across four continents in more than a dozen countries worldwide. For more information, visit:
https://www.scopely.com/
.
Notice to Candidates: Scopely will never request payment or financial information during the application or hiring process. Please apply only through our official
website
and verify that all Talent Partner communications come from an email address ending in @
scopely.com
.
Should you have any questions or encounter any fraudulent requests/emails/websites, please immediately contact recruiting@scopely.com. Our job applicant privacy policies are available here:
California Privacy Notice
and
EEA/UK Privacy Notice
.
Employment at Scopely is based solely on a person's merit and qualifications. Scopely does not discriminate against any employee or applicant because of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), or any other basis protected by law. We also consider qualified applicants with arrest or conviction records, consistent with applicable federal, state and local law.
Location: Limassol, Cyprus
Workplace: on-site
Mayflower is a technology company building highload products used by millions of people worldwide. Operating at the scale of one of the world's top-50 websites, we solve complex engineering challenges and create solutions that power real-time entertainment for a global audience.
Now we look for a
Data Scientist
to join our ML team
Job Responsibilities
Search & Retrieval
Develop and improve retrieval pipelines for large-scale production search systems.
Work on candidate generation, query processing, matching, filtering, and retrieval strategies.
Improve search relevance, result coverage, and overall SERP quality.
Analyse failed searches, irrelevant results, zero-result queries, and other search-quality issues.
Explore lexical, semantic, behavioural, hybrid, and vector search approaches.
Ranking & Relevance
Build, train, and optimise ranking models for search and recommendation systems.
Develop learning-to-rank solutions using behavioural, content-based, contextual, and real-time features.
Design ranking features based on clicks, conversions, popularity, freshness, availability, and user behaviour.
Evaluate ranking quality using Precision, Recall, NDCG, MAP, MRR, and related relevance metrics.
Optimise models for low-latency inference and investigate relevance degradation, bias, and feedback loops.
Recommendation Systems
Develop recommendation models and candidate-generation strategies for personalised and non-personalised scenarios.
Build recall and ranking stages for multi-stage recommendation pipelines.
Work on related-item, complementary-item, next-action, and behavioural recommendation use cases.
Develop user, item, session, and contextual representations.
Balance relevance, diversity, novelty, coverage, and business constraints.
Experimentation & Evaluation
Design and run offline and online experiments for search, ranking, and recommendation improvements.
Build evaluation frameworks that connect model quality with product and business outcomes.
Design and analyse A/B tests using CTR, conversion, engagement, retention, and revenue-related metrics.
Create reproducible pipelines for data preparation, model training, evaluation, and comparison.
Evaluate model robustness across traffic segments, query groups, user cohorts, and edge cases.
ML Pipelines & Collaboration
Build end-to-end ML pipelines for feature generation, training, validation, deployment, and monitoring.
Work with high-load, real-time, and low-latency production systems.
Process large datasets using Python, SQL, batch pipelines, streaming systems, and Kafka.
Collaborate with product, backend, data engineering, and MLOps teams to productionise ML solutions.
Communicate technical decisions, experiment results, and trade-offs while contributing to ML best practices.
You’ll thrive here if you have
Strong hands-on experience building production search, ranking, or recommendation systems.
Strong Python and SQL skills for machine learning, data processing, and analytical queries.
Practical experience with learning-to-rank, candidate retrieval, search relevance, or recommender-system modelling.
Experience building and evaluating multi-stage retrieval and ranking pipelines.
Strong understanding of search and recommendation metrics, including Precision, Recall, NDCG, MAP, MRR, CTR, and conversion.
Experience with feature engineering and behavioural data such as impressions, clicks, sessions, and conversions.
Experience with ML libraries such as scikit-learn, XGBoost, LightGBM, CatBoost, PyTorch, or TensorFlow.
Experience working with large-scale production systems, distributed data processing, analytical databases, and streaming platforms.
Strong understanding of experimentation and A/B testing, with the ability to independently build, and validate ML solutions.
That can be a plus:
Experience with Elasticsearch, OpenSearch, Solr, Lucene, or another search-engine stack.
Experience with vector databases, approximate nearest neighbour search, and hybrid lexical-semantic retrieval.
Experience with query understanding, classification, spell correction, synonyms, or query expansion.
Experience with DSSM, two-tower models, BERT-based ranking, cross-encoders, or similar neural architectures.
Experience with large-scale data and ML platforms such as Airflow, MLflow
Conditions
We know that great talent deserves great conditions, so here's what you can expect when joining us:
EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family.
Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free.
Transparent performance reviews twice a year, with bonus opportunities and salary adjustments.
Private medical insurance for you and your family, a corporate mobile plan (unlimited in Cyprus with roaming included), and interest-free support for car purchases.
Provident fund (Cypus): a long-term savings plan co-funded by you and the Company together (available after probation) that grows throughout your time with us in Cyprus.
Mindfulness & well-being support, including psychological assistance with 50% coverage.
50% coverage of school and kindergarten fees for your children.
Fully covered sports benefits, and also access to in-house electric scooters and bike rentals, and cycling purchase compensation.
Investment in your growth: paid language courses and access to suited-for-you development programs, including conferences, training programs, and coaching to support your professional journey.
A culture of recognition: a peer reward program to celebrate your contributions.
A fully equipped office in Limassol’s city center, with everything you need for deep work and collaboration.
Free catering in the office and an in-house coffee bar with high-quality drinks and a health bar stocked with nutritious snacks.
A strong engineering culture: international teams, corporate events, team buildings, and hackathons—because great work happens in great communities.
Recruitment process
HR interview (40 min);
Technical interview (1.5 hour);
Final interview (45 min).
Задачи:
— Конфигурировать и разворачивать инфраструктурные компоненты
— Адаптировать/разрабатывать с нуля автоматизированные пайплайны под актуальные бизнес-задачи (AutoML, LLM, computer vision и пр)
— Создавать и поддерживать пользовательские инструменты для работы в едином ML-контуре применения и обучения
— Масштабировать разрабатываемые системы и инструменты для управления жизненным циклом моделей машинного обучения
Требования:
— Опыт DevOps от 3х лет (Docker, Helm, Jenkins/GitLab CI, Python)
— Опыт ML/MLOps от 1 года (Airflow, JupyterHub, MLflow, Seldon, CUDA)
— Опыт администрирования Kubernetes от 2х лет
— Опыт работы с Hadoop, Spark, Kafka, ELK
Условия:
— Работа в аккредитованной IT компании, имеющей собственные продукты
— Формат работы: удаленный по РФ
— Предоставляем расширенный ДМС (со стоматологией)
— Выдаем необходимую для работы технику (ноутбук)
— Возможность воспользоваться реферальной программой: “Приведи товарища”
— Участие в Бонусной программе
— Помогаем в ипотеке и других пособиях
— Предоставляем возможность построить карьеру в рамках ведущих компаний России
Location: Los Angeles, USA
At Riot, Data Engineers play a critical role in transforming data into actionable insights that drive decisions across the company. Our engineers are deeply player-focused and collaborate across diverse teams to enhance the experiences of millions of players worldwide.
As a
Senior Data Engineering Manager
within VALORANT, you will be shaping the direction of the game by working with designers, product managers, data scientists, analysts, and engineers using data to better serve and understand our game and our players. This role is designed for an engineering leader who thrives in ambiguous environments, takes initiative to solve real problems quickly, and enjoys wearing multiple hats. As one of the senior-most data leaders on the game team, you will influence how data is managed and used across the studio.
Responsibilities:
Manage a team of 5 data engineers, provide them career coaching and growth opportunities, and ensure all work is aligned with business needs.
Partner with leaders in analytics, data science, and product disciplines to align on the most important data engineering projects and collaborate with them through all phases of the development and operational lifecycle.
Set the technical direction of the team, including processes and tooling.
Be accountable for the technical health of products owned by the team.
Working with other engineers, standardize best practices for instrumentation, telemetry, and metrics collection
Ensure data quality, governance, and compliance with regulatory standards (e.g., GDPR, CCPA).
Support cost optimization by ensuring scalable and efficient data solutions.
Build healthy relationships with data engineering teams across Riot, and lead by shaping infrastructure, craft standards, tooling, and organizational best practices.
Required Qualifications:
Bachelor's or Master’s degree in Computer Science, Information Systems, Engineering, or a related field.
10+ years experience in data engineering or a related field. 5+ years managing a team.
Hands-on expertise in big-data technologies, particularly the Apache stack (Airflow, Spark, etc).
Proficiency in cloud infrastructure (AWS or GCP) and Databricks.
Expertise in designing efficient and scalable data models with large data sets across multiple teams and in collaboration with insights or data stakeholders.
Demonstrated ability to work cross-functionally with engineering, analytics, and product teams.
Experience mentoring and guiding other engineers.
Desired Qualifications:
2+ years of experience in data engineering for major video game titles.
1+ years experience working with DBT in a production environment
Experience using analytics to drive gameplay and feature changes (ideally from game dev through launch)
Experience working in close partnership with data analysts or product managers.
For this role, you'll find success through craft expertise, a collaborative spirit, and decision-making that prioritizes the delight of players. We will be looking at your past studies, experience, and your personal relationship with games. If you embody player empathy and care about players' experiences, this could be your role!
Our Perks:
Riot focuses on work/life balance, shown by our open paid time off policy and other perks such as flexible work schedules. We offer medical, dental, and life insurance, parental leave for you, your spouse/domestic partner, and children, and a 401k with company match. Check out our
benefits pages
for more information.
At Riot Games, we
put players first
. That mission drives every decision in our quest to create games and experiences that make it better to be a player. Whether you’re working directly on a new player-facing experience or you’re supporting the company as a whole, everyone at Riot is part of our mission. And just like in our games, we’re better when we work together. Our goal is to create collaborative teams where you are empowered to bring your unique perspective everyday. If that sounds like the kind of place you want to work, we’re looking forward to your application.
It’s our policy to provide equal employment opportunity for all applicants and members of Riot Games, Inc. Riot Games makes reasonable accommodations for handicapped and disabled Rioters and does not unlawfully discriminate on the basis of race, color, religion, sex, sexual orientation, gender identity or expression, national origin, age, handicap, veteran status, marital status, criminal history, or any other category protected by applicable federal and state law. We consider for employment all qualified applicants, including those with criminal histories, in a manner consistent with applicable federal, state and local law, including the California Fair Chance Act, the City of Los Angeles Fair Chance Initiative for Hiring Ordinance, the Los Angeles County Fair Chance Ordinance for Employers, the San Francisco Fair Chance Ordinance, and the Washington Fair Chance Act.
Per the Los Angeles County Fair Chance Ordinance, the following core duties may create a basis for disqualifying candidates with relevant criminal histories:
Safeguarding confidential and sensitive Company data
Communication with others, including Rioters and third parties such as vendors, and/or players, including minors
Accessing Company assets, secure digital systems, and networks
Ensuring a safe interactive environment for players and other Rioters
These duties are directly related to essential operations, safety, trust, and compliance obligations within our organization. Please note that job duties may evolve based on business needs and additional responsibilities may be assigned as necessary to maintain operational efficiency and security.
Location: Dublin, Ireland; London, England
Fin
, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.
Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system.
Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI.
Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce.
GTM Engineer
GTM Engineer (Applied AI)
Location: Dublin or London
About Fin
Fin, now part of Salesforce, is on a mission to help businesses provide perfect customer experiences.
Our AI Agent Fin is the highest-performing AI Customer Agent on the market today, enabling businesses to deliver impeccable, always-on customer support across the customer journey, from service, to sales, to ecommerce. Powered by our own AI models, Fin resolves complex customer issues end-to-end across every channel, with minimal set-up and integration. Fin can also be combined with our natively integrated Intercom help desk, giving modern support teams one single system.
Together with Salesforce, the #1 AI CRM, where humans with agents drive customer success, we're building the future of customer experience. Here, ambition meets action. Tech meets trust. And innovation isn't a buzzword, it's a way of life. The world of work as we know it is changing, and we're looking for Trailblazers who are passionate about bettering business and the world through AI.
Ready to level up your career at the company leading workforce transformation in the agentic era? You're in the right place. Agentforce is the future of AI, and you are the future of Salesforce.
The team
GTM Engineering builds the tools that help our Sales and Customer Success teams win more deals, grow accounts and keep customers. The aim is tools that make a real difference to pipeline, win rate and retention, and give reps more time with customers.
To do that, we join data most GTM tools never see: how customers use the product, what was said on every sales call, how Fin performs for each customer, and everything in the CRM. On top of that we build agents and models that tell reps which accounts need attention, prepare them for calls, flag buying and churn signals, explain why deals are won and lost, and draft research and outreach.
The role
We're looking for a GTM Engineer to own a business problem from start to finish. You'll start with a commercial question or problem, you'll work out with reps and leaders whether it's worth solving and what success looks like. Then you'll build the data, the agent and the product, and get it into the daily routine of the people it's for.
Once it's live, you'll own making it better. You'll understand how it behaves in production, find where it fails, improve how it decides or acts, and work out whether it's making a difference. That includes deciding when something isn't working and should stop.
What you'll do:
Build and ship AI agents and LLM-powered tools for Sales and Success, such as account research, call prep, post-call follow-up, renewal risk and pipeline review.
Own the full stack: Python backends and APIs, data models in Snowflake, feedback pipelines, and React frontends where a tool needs one.
Instrument what you build. Trace agent actions, tool calls, failures and the edits reps make to agent output, so you can see where quality breaks down.
Set the quality bar with the people who use the tools. Build evaluation sets, grade output with human and model graders, and run regression tests and production monitoring.
Diagnose weak results across context, data, tools, prompts and workflow design. Test the fix on replays of past traffic before it ships.
Decide what an agent can do on its own and where a rep reviews its work first, and build the guardrails and review steps to match.
Measure adoption and business impact on conversion, win rate, cycle time and retention. Use experiments and staged rollouts where you can.
Get tools into teams' hands. Write the playbook, run the enablement session, and work with sales leaders so the tool becomes part of how their team works.
What you bring
4+ years building production software, applied AI systems or data products.
You've built LLM-powered applications or agents that real users rely on.
You've improved an AI system after launch using traces, user feedback, evals or experiments.
Hands-on evaluation experience, such as building regression tests and grading output with humans or models.
Strong Python and SQL. You're comfortable designing APIs and data models.
You can measure impact with rigour and tell whether a metric moved because of your change.
Product judgment. You can sit with a sales rep, work out what they need, and decide what to build first.
You use AI coding tools heavily and know how to get reliable work out of them.
Nice to have
Experience with GTM systems such as Salesforce, Gong or Outreach.
dbt, Airflow or other data orchestration tools.
Agent evaluation or observability tools.
Time spent in, or building for, a sales, CS or revenue operations team.
Unleash Your Potential
When you join Salesforce, you’ll be limitless in all areas of your life. Our benefits and resources support you to find balance and be your best, and our AI agents accelerate your impact so you can do your best. Together, we’ll bring the power of Agentforce to organizations of all sizes and deliver amazing experiences that customers love. Apply today to not only shape the future — but to redefine what’s possible — for yourself, for AI, and the world.
In the United States, compensation offered will be determined by factors such as location, job level, job-related knowledge, skills, and experience. Certain roles may be eligible for incentive compensation, equity, and benefits. At Fin, we want to give people what they need to do the best work of their careers. Our benefits and programs are designed to support your health and wellbeing, your family, your time away from work, and your financial future. Offerings vary by location in line with local practices and requirements. Learn more about working at Fin and the benefits we offer at
fin.ai/careers
. Pursuant to the San Francisco Fair Chance Ordinance and the Los Angeles Fair Chance Initiative for Hiring, Salesforce will consider for employment qualified applicants with arrest and conviction records.
Policies
Fin has a hybrid working policy. We believe that working in person helps us stay connected, collaborate easier and create a great culture while still providing flexibility to work from home. We expect employees to be in the office at least three days per week.
We have a radically open and accepting culture at Fin. We avoid spending time on divisive subjects to foster a safe and cohesive work environment for everyone. As an organization, our policy is to not advocate on behalf of the company or our employees on any social or political topics out of our internal or external communications. We respect personal opinion and expression on these topics on personal social platforms on personal time, and do not challenge or confront anyone for their views on non-work related topics. Our goal is to focus on doing incredible work to achieve our goals and unite the company through our
core values
.
Salesforce is an equal opportunity employer and maintains a policy of non-discrimination with all employees and applicants for employment. What does that mean exactly? It means that at Salesforce, we believe in equality for all. And we believe we can lead the path to equality in part by creating a workplace that’s inclusive, and free from discrimination.
Know your rights: workplace discrimination is illegal.
Any employee or potential employee will be assessed on the basis of merit, competence and qualifications – without regard to race, religion, color, national origin, sex, sexual orientation, gender expression or identity, transgender status, age, disability, veteran or marital status, political viewpoint, or other classifications protected by law. This policy applies to current and prospective employees, no matter where they are in their Salesforce employment journey. It also applies to recruiting, hiring, job assignment, compensation, promotion, benefits, training, assessment of job performance, discipline, termination, and everything in between. Recruiting, hiring, and promotion decisions at Salesforce are fair and based on merit. The same goes for compensation, benefits, promotions, transfers, reduction in workforce, recall, training, and education.
Location: Remote - United States
Reddit is a community of communities. It’s built on shared interests, passion, and trust, and is home to the most open and authentic conversations on the internet. Every day, Reddit users submit, vote, and comment on the topics they care most about. With 100,000+ active communities and approximately 130 million daily active unique visitors, Reddit is one of the internet’s largest sources of information. For more information, visit
www.redditinc.com
.
At Reddit, machine learning sits at the heart of how millions of people discover, connect, and engage with the world’s largest collection of human conversations. From powering personalized recommendations and search to optimizing advertising systems and marketplace dynamics, our ML engineers tackle some of the most interesting and impactful problems in large-scale applied machine learning.
We are hiring Machine Learning Engineers across our Consumer Engineering organization, giving you the opportunity to work on a wide range of high-impact problems across the Consumer ecosystem. We are looking for Machine Learning Engineers who are excited to build systems end-to-end, from research and modeling to production deployment, and who want to help shape the future of discovery, relevance, and monetization at Reddit.
If you love working on complex, real-world ML problems at massive scale, this role is for you.
What You’ll Work On
We are looking for a Staff Machine Learning Engineer to help drive the next generation of Reddit’s ML ecosystem across recommendations, search, messaging, and foundational AI systems. You will lead high-impact initiatives from ideation to production, shaping both technical strategy and product direction across multiple ML domains. This is a highly cross-functional role partnering with Product, Data Science, and Engineering to deliver meaningful user and business impact.
This role sits at the intersection of:
Relevance & recommendation systems (content, search, notifications)
AI-powered discovery & LLM-driven experiences
Content and user understanding & large-scale representation learning
Large-scale ML infrastructure and pipelines
What You’ll Do
Lead end-to-end ML initiatives from ideation through production and iteration, shaping technical direction and translating product goals into scalable solutions
Architect, build and deploy large-scale ML systems across recommendation, search, and content/user understanding, including retrieval/ranking models, representation learnings embeddings optimizations, and LLM or GenAI-powered capabilities
Drive measurable impact on user engagement, discovery, and long-term value
Collaborate with cross-functional teams to align product and technical roadmaps and unlock key future ML capabilities
Stay at the forefront of AI research, evaluating and introducing new AI/ML paradigms to keep Reddit’s ML ecosystem at the cutting edge
Contribute to the development of best practices, guidelines, and ethical AI principles for responsible LLM development and deployment
Mentor and guide senior and mid-level ML engineers, fostering a culture of excellence, innovation, and knowledge sharing
Set technical vision and drive technical discussions, present findings to leadership, and contribute to long-term ML planning and decision-making
Required Qualifications
7+ years of experience building, deploying, and operating machine learning systems in production
Deep understanding of machine learning methods, spanning classical approaches and modern deep learning (e.g., Transformers, GNN, etc)
Expert at developing and productionizing models using TensorFlow, PyTorch, or Hugging Face Transformers
Experience building production-quality code incorporating testing, evaluation, and monitoring using object-oriented programming, including experience in Python and Golang
Experience designing and scaling ML systems, including data pipelines, feature engineering, model training/serving, and production monitoring
Excellent communication and collaboration skills, with the ability to discuss complex technical topics with diverse teams and translating product needs into scalable ML solutions
Track record of driving measurable impact through applied machine learning in real-world products
Preferred Qualifications
Subject matter expertise in one of the following domains:
Recommender systems
Search systems (lexical and semantic retrieval and ranking)
Content understanding (NLU/NLP/LLM, topic/taxonomy modeling, interest graphs or clustering, and multimodal understanding)
Familiarity with distributed systems and large-scale data processing frameworks (Spark, Kafka, Ray, Airflow, BigQuery, Redis, etc.)
Experience working with real-time systems and low-latency production environments
Experience with LLM/GenAI techniques, including but not limited to LLM evaluation, alignment, fine-tuning, knowledge distillation, RAG/agentic systems and productionizing LLM-powered products at scale
Strong experimentation rigor, with experience formulating clear hypotheses, designing actionable learning plans and building offline/online correlations
Advanced degree in Computer Science, Machine Learning, or related quantitative field
Potential Teams
Home Experience
ML Understanding
Feed Relevance
Answer Experience
Search and Answers Relevance
Search Experience
Benefits
Comprehensive Healthcare Benefits and Income Replacement Programs
401k with Employer Match
Global Benefit programs that fit your lifestyle, from workspace to professional development to caregiving support
Family Planning Support
Gender-Affirming Care
Mental Health & Coaching Benefits
Flexible Vacation & Paid Volunteer Time Off
Generous Paid Parental Leave
#LI-Remote
Pay Transparency:
This job posting may span more than one career level.
In addition to base salary, this job is eligible to receive equity in the form of restricted stock units, and depending on the position offered, it may also be eligible to receive a commission. Additionally, Reddit offers a wide range of benefits to U.S.-based employees, including medical, dental, and vision insurance, 401(k) program with employer match, generous time off for vacation, and parental leave. To learn more, please visit
https://www.redditinc.com/careers/
.
To provide greater transparency to candidates, we share base salary ranges for all US-based job postings regardless of state. We set standard base pay ranges for all roles based on function, level, and country location, benchmarked against similar stage growth companies. Final offer amounts are determined by multiple factors including, skills, depth of work experience and relevant licenses/credentials, and may vary from the amounts listed below.
The base salary range for this position is:
$230,000
—
$322,000 USD
In select roles and locations, the interviews will be recorded, transcribed and summarized by artificial intelligence (AI). You will have the opportunity to opt out of recording, transcription and summarization prior to any scheduled interviews.
During the interview, we will collect the following categories of personal information: Identifiers, Professional and Employment-Related Information, Sensory Information (audio/video recording), and any other categories of personal information you choose to share with us. We will use this information to evaluate your application for employment or an independent contractor role, as applicable. We will not sell your personal information or disclose it to any third party for their marketing purposes. We will delete any recording of your interview promptly after making a hiring decision. For more information about how we will handle your personal information, including our retention of it, please refer to our
Candidate Privacy Policy for Potential Employees and Contractors
.
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Location: Chicago
DRW
is a diversified trading firm with over 3 decades of experience bringing sophisticated technology and exceptional people together to operate in markets around the world. We value autonomy and the ability to quickly pivot to capture opportunities, so we operate using our own capital and trading at our own risk.
Headquartered in Chicago with offices throughout the U.S., Canada, Europe, and Asia, we trade a variety of asset classes including Fixed Income, ETFs, Equities, FX, Commodities and Energy across all major global markets. We have also leveraged our expertise and technology to expand into three non-traditional strategies: real estate, venture capital and cryptoassets.
We operate with respect, curiosity and open minds. The people who thrive here share our belief that it’s not just what we do that matters–it's how we do it.
DRW
is a place of high expectations, integrity, innovation and a willingness to challenge consensus.
About the Team
The DRW C/Options Data Engineering team is essential to developing valuable datasets and scalable data infrastructure critical to our trading operations. We work closely with traders, researchers, and other engineering teams to ensure seamless data flow and accessibility, supporting data-driven decision-making. Our systems are designed to handle large volumes of data, maintain quality and integrity, and provide robust APIs for fast, ergonomic data retrieval.
About the Role
In this role you will:
Collaborate with cross-functional teams to deliver data solutions that support diverse trading activities.
Take full ownership of data products, guiding them from initial concept through to stable production.
Design, build, and maintain systems for both batch processing and real-time streaming of time series datasets, ensuring high data quality and reliability.
Develop APIs and data access methods for fast, intuitive retrieval of historical and live data, working with both new and existing systems.
Provide on-call support as needed.
Qualifications:
A minimum of 2+ years’ experience using at least one of Python, Java, and C++, and can work comfortably in multiple programming languages
A track record of working directly with end customers, scoping and delivering production systems in fast-moving and ambiguous environments
Ability to dive deep into complex problems, develop intuitive understandings, spot risks early, and minimize complexity
Exceptional interpersonal skills - you communicate clearly with stakeholders as well as other engineers, fostering a collaborative, supportive working environment
Experience in the financial markets, especially in delta one, store of value, and/or FICC options trading
Experience with Linux-based, concurrent, high-throughput, low-latency software systems
Experience with pipeline orchestration frameworks (e.g. Airflow, Dagster)
Experience with streaming platforms (e.g. Kafka), data lake platforms (e.g. Delta Lake, Apache Iceberg), and relational databases
Have a Bachelors or advanced degree in Computer Science, Mathematics, Statistics, Physics, Engineering, or equivalent work experience
The annual base salary range for this position is $175,000 $225,000 depending on the candidate’s experience, qualifications, and relevant skill set. The position is also eligible for an annual discretionary bonus. In addition, DRW offers a comprehensive suite of employee benefits including group medical, pharmacy, dental and vision insurance, 401k (with discretionary employer match), short and long-term disability, life and AD&D insurance, health savings accounts, and flexible spending accounts.
For more information about DRW's processing activities and our use of job applicants' data, please view our Privacy Notice at
https://drw.com/privacy-notice
.
California residents, please review the California Privacy Notice for information about certain legal rights at
https://drw.com/california-privacy-notice
.
#LI-BL1
Location: Hong Kong, Hong Kong SAR; Singapore, Singapore
Who We Are
At OKX, we believe that the future will be reshaped by crypto, and ultimately contribute to every individual's freedom.
OKX is a leading crypto exchange, and the developer of OKX Wallet, giving millions access to crypto trading and decentralized crypto applications (dApps). OKX is also a trusted brand by hundreds of large institutions seeking access to crypto markets. We are safe and reliable, backed by our Proof of Reserves.
Across our multiple offices globally, we are united by our core principles: We Before Me, Do the Right Thing, and Get Things Done. These shared values drive our culture, shape our processes, and foster a friendly, rewarding, and diverse environment for every OK-er.
OKX is part of OKG, a group that brings the value of Blockchain to users around the world, through our leading products OKX, OKX Wallet, OKLink and more.
About the Team
We sit on the front lines of OKX's security and compliance mission. Our charter is to build the flexible, scalable, and intelligent AI systems that detect and prevent identity fraud, account takeover, and large-scale organized abuse — in real time and at the scale of a global financial platform. We own the core identity-risk capabilities that decide, millions of times a day, whether an account can be trusted: identity trust signals, behavioral risk modeling, relationship and cluster intelligence, and face, liveness and document verification. We work shoulder-to-shoulder with Product, Risk, Compliance, and Engineering to turn the hardest adversarial problems in crypto into production-grade defenses that protect good users and the open financial system.
About the Role
We are looking for a Senior AI Engineer to design, build, and own key identity-risk and trust models at OKX. You will build models that combine identity verification results, device and geo data, and user behavior into trust and risk signals, and use graph and clustering methods to uncover organized, industrialized fraud. This is an end-to-end, research-to-production role: you will own algorithms in your domain and ship models into real-money, high-risk, large-scale production environments.
You will be a hands-on technical contributor who works closely with Product, Risk, and Compliance, and who helps raise the technical bar of the team. Your domains span:
Identity trust & risk modeling
— fusing verification scores, device, geo, and behavioral data into identity-quality and trust signals.
Cluster & relationship intelligence
— graph and clustering methods to identify account farms, mass registration, and coordinated attacks.
Behavioral risk modeling
— behavioral features and sequence models for account takeover and abnormal-session detection.
Biometric & multimodal signals
— face embeddings, liveness/anti-spoofing, DeepFake and injection defense, document forgery and AIGC detection, used as inputs to identity trust and the risk layer.
AI agents
— applying agentic AI to scale investigation, detection, and operational defense.
What You'll Be Doing
Build identity trust & risk models:
Design and ship coarse-to-fine risk models that fuse face/liveness/document verification scores, device, IP and geo signals, and behavioral data, for high-concurrency real-time decisioning.
Uncover organized
fraud
with graph & clustering:
Build entity graphs across accounts, devices, faces, documents and templates, and apply community detection, clustering, and GNN methods to detect fraud rings and large-scale abuse.
Develop behavioral features & sequence models:
Engineer real-time and offline behavioral features, and build sequence models to detect account takeover, bot/script behavior, and abnormal sessions.
Leverage biometric & multimodal signals:
Turn biometric features (face embeddings, face quality, liveness and anti-spoofing results) and document-forgery and DeepFake signals into reliable identity-trust inputs for risk decisions, including biometric similarity for cross-account linkage and duplicate-identity detection. Work with the face, liveness, and document teams, or build models yourself.
Drive execution & collaboration:
Deliver measurable results while managing ambiguity; partner with backend, product, infrastructure, risk, and compliance teams to integrate models into the production decision chain. Own metric definitions, the balance between false positives and missed fraud, pass rate, monitoring, and drift handling.
Advance applied R&D:
Experiment with graph learning, multimodal fusion, and AI agents; stay current with academic and industry advances and translate them into practical defenses.
Raise the technical bar:
Contribute to design reviews, share applied-AI best practices, and mentor junior engineers.
What We Look For
5+ years
of hands-on experience building risk-control, fraud-detection, or identity-trust models, including significant experience deploying ML systems into production.
Graph & clustering expertise:
Experience applying graph mining, community detection, clustering, or GNN methods to fraud or abuse detection.
Behavioral modeling:
Solid experience with behavioral feature engineering and sequence modeling, including real-time feature pipelines.
Deep AI/ML expertise:
Strong proficiency with PyTorch and/or TensorFlow, and solid experience with production ML systems.
Strong technical & coding skills:
Strong coding ability (e.g., Python, SQL) and the system-level thinking to design end-to-end solutions with high availability and low latency.
Adversarial mindset:
Understanding of how fraudsters adapt, and how to evaluate and iterate defenses against evolving attacks.
Collaboration:
Strong communication skills, with experience working across engineering, product, and risk teams.
Education:
Bachelor's degree or higher in Computer Science, Electrical Engineering, or a related field.
Preferred Qualifications
Experience in identity verification, KYC/KYB, AML, face-payment or payment risk control, or biometric security.
Hands-on experience with face recognition, liveness/anti-spoofing, OCR, document parsing, fake-ID detection, or media forensics.
Experience with graph databases or graph computing (e.g., Neo4j, GraphX) and real-time graph features.
Knowledge of data and AI/ML infrastructure (e.g., Spark, Flink, Kafka, Airflow, Snowflake).
Familiarity with MLOps best practices: monitoring, retraining, and continuous improvement of production models.
Experience with LLMs and AI agents.
Experience working in fast-paced technology companies or security-critical environments.
Research publications, patents, or open-source contributions in relevant AI fields.
Perks & Benefits
Competitive total compensation package
L&D programs and Education subsidy for employees' growth and development
Various team building programs and company events
Wellness and meal allowances
Comprehensive healthcare schemes for employees and dependants
More that we love to tell you along the process!
Notice:
All official
OKX
vacancies are published on this website.
While roles may appear on selected third-party platforms from time to time, information on other sites may be inaccurate or outdated.
If in doubt, please apply directly through our official careers website.
Information collected and processed as part of the recruitment process of any job application you choose to submit is subject to
OKX
's
Candidate Privacy Notice
.
Location: San Francisco; New York
Workplace: Hybrid
ABOUT BASETEN
Baseten powers mission-critical inference for the world's most dynamic AI companies, like Cursor, Notion, OpenEvidence, Abridge, Clay, Gamma, and Writer. By uniting applied AI research, flexible infrastructure, and seamless developer tooling, we enable companies operating at the frontier of AI to bring cutting-edge models into production. We're growing quickly and recently raised our $1.5B Series F https://www.baseten.co/blog/announcing-our-series-f/, led by Altimeter Capital, Conviction Partners, and Spark Capital. Join us and help build the platform engineers turn to ship AI products.
THE ROLE
We’re hiring a Data Engineer to build and scale Baseten’s internal data platform. This role sits at the intersection of data engineering, analytics, and data science, transforming raw product and business data into reliable datasets that power decision-making.
You’ll design the data models, pipelines, and analytics infrastructure that enable teams across Product, Engineering, Finance, Marketing, and Sales to understand usage and performance. This includes working with AI inference, infrastructure, and observability data to generate insights about the product, business operations and platform economics.
You’ll partner closely with stakeholders to build robust, scalable pipelines, define company-wide metrics that inform strategy and planning.
RESPONSIBILITIES
- Design and maintain core data models and semantic layers
- Develop and orchestrate batch and streaming data pipelines using technologies such as Apache Beam, Kafka, Airflow, or similar frameworks
- Analyze inference and infrastructure telemetry, including data from OpenTelemetry, Grafana, and other observability tools
- Define and maintain company-wide metrics across product usage, performance, and customer lifecycle
- Enable self-service analytics through agents and tools, with well-structured semantic layers and context
- Ensure data reliability and quality through testing, documentation, and governance
PREFERRED QUALIFICATIONS
- Understanding of inference metrics such as latency, throughput, token usage, and model performance
- Experience supporting B2B SaaS and/or consumption-based platforms
- Application of forecasting and predictive modeling (e.g., ARIMA, Prophet) to business processes
BENEFITS
- Competitive compensation, including meaningful equity
- (U.S. only) 100% coverage of medical, dental, and vision insurance for employee and dependents
- Flexible PTO policy including company wide Winter Break (our offices are closed from Christmas Eve to New Year's Day!)
- Paid parental leave
- Fertility and family-building stipend through Carrot
- (U.S. only) Company-facilitated 401(k)
- Exposure to a variety of ML startups, offering unparalleled learning and networking opportunities.
Apply now to embark on a rewarding journey in shaping the future of AI! If you are a motivated individual with a passion for machine learning and a desire to be part of a collaborative and forward-thinking team, we would love to hear from you.
At Baseten, we are committed to fostering a diverse and inclusive workplace. We provide equal employment opportunities to all employees and applicants without regard to race, color, religion, gender, sexual orientation, gender identity or expression, national origin, age, genetic information, disability, or veteran status.
We are an Equal Opportunity Employer and will consider qualified applicants with criminal histories in a manner consistent with applicable law (by example, the requirements of the San Francisco Fair Chance Ordinance, where applicable).
Location: Kyiv
Workplace: onsite
Ajax Systems — міжнародна технологічна компанія і найбільший у Європі виробник охоронних систем. Продуктам Ajax довіряють понад 4,5 мільйона кінцевих користувачів і 330 тисяч PRO-користувачів у більш ніж 180 країнах. Компанія пропонує комплексні рішення для захисту житлових і комерційних об'єктів різного масштабу. Нині портфоліо Ajax налічує понад 280 пристроїв для захисту від вторгнення, відеоспостереження, пожежної безпеки, комфорту та автоматизації. Щороку ми демонструємо кратне зростання як команди, так і кількості користувачів у всьому світі.
Наразі ми шукаємо Спеціаліста з аналітики даних, який допоможе розвивати автоматизовану звітність та аналітичні інструменти для підтримки виробництва високотехнологічної електроніки. У цій ролі ти працюватимеш на перетині різних відділів, створюючи рішення для підвищення ефективності процесів, автоматизації рутинних задач та побудови прозорої системи мотивації на основі даних.
Обов’язки:
Збір і обробка даних із різних джерел: бази даних, ERP,
Google Sheets
, API.
Побудова дашбордів для ефективної передачі інформації за допомогою
Power BI.
Підтримка та розвиток регулярної звітності (бюджетування виробництва, звіти якості, операційні та мотиваційні метрики).
Аналіз бізнес-процесів та пошук можливостей їх оцифровки й автоматизації.
Розробка інструментів введення даних Google Sheets для планування, або фіксації результатів роботи.
Розробка інструментів введення або обміну даними (Telegram-боти,
FastAPI
-сервіси, інші інтеграційні рішення) — як зона росту.
Документування логіки розрахунків, джерел даних та структури звітності.
Розвиток напрямку роботи з хмарними сервісами та сучасною data-інфраструктурою в команді аналітики (Databricks / Airflow).
Вимоги:
Практичний досвід роботи з
Power BI
,
DAX
та
SQL.
Практичний досвід роботи з
Google Sheets
; знайомство з
Google Apps Script
або
JavaScript
буде плюсом.
Базові навички
Python
для обробки та автоматизації даних; пет-проєкти та досвід роботи з API будуть плюсом.
Розуміння принципів автоматизації звітності та роботи з даними.
Англійська на рівні впевненого читання технічної документації.
Ми пропонуємо:
Роботу у стабільній технологічній компанії з реальним впливом на виробничі процеси.
Офіційне працевлаштування та оплачувану відпустку.
Конкурентну заробітну плату.
Медичне страхування.
Корпоративне вивчення англійської мови.
Компенсацію профільного навчання.
Можливість участі у бета-тестуванні нових продуктів Ajax до їх релізу.
Простір для розвитку у напрямку автоматизації та дата-інженерії.
Якщо ти готовий приєднатися до нашої команди — чекаємо на твоє резюме!
Location: Mexico; Colombia; Argentina; Brazil; Costa Rica
Our client engineers and manufactures modular infrastructure supporting backup power systems, data centers, and industrial facilities. These platforms integrate generators, cooling systems, exhaust systems, structural enclosures, and electrical infrastructure into prefabricated power modules designed for standby power, microgrids, and mission-critical applications.
Position Overview
We are seeking a
Senior Mechanical Engineer
to lead the mechanical design of modular generator systems. This role focuses on the integration and packaging of diesel or gas generator equipment, cooling systems, exhaust systems, and structural frames into factory-built modular power platforms.
The engineer will work closely with electrical engineering, manufacturing, and integration teams to deliver production-ready generator modules designed for reliability, serviceability, and efficient manufacturing.
Requirements
Design generator enclosures, equipment skids, and structural steel frames supporting large engine-driven power systems
Package engines, alternators, radiators, exhaust systems, and associated mechanical equipment within modular enclosures
Perform structural analysis of heavy equipment mounting structures, lifting frames, and transport loads
Design ventilation and airflow systems supporting generator cooling and heat rejection
Conduct CFD or airflow analysis to validate cooling performance and thermal management
Develop manufacturable weldments, sheet metal assemblies, and structural components
Design service access, maintenance pathways, and equipment layout for field operations
Coordinate mechanical systems with electrical switchgear, control panels, and cable routing zones
Support prototype builds, testing, and manufacturing integration of generator platforms
Lead root cause investigations related to vibration, structural behavior, or thermal performance
Required Qualifications
Bachelor’s degree in Mechanical Engineering
7+ years of experience in mechanical design for industrial equipment, power systems, or heavy machinery
Strong experience designing structural steel assemblies and heavy equipment packaging
Proficiency with
SolidWorks
for large assemblies and mechanical system integration
Experience with airflow, cooling, or thermal analysis for industrial equipment
Preferred Qualifications
Experience with
generator systems or engine-driven power equipment
Experience designing
modular or containerized industrial systems
Familiarity with
standby power infrastructure
, including data centers or critical facilities
Experience supporting prototype builds and manufacturing environments
Benefits
Work for the most exciting companies in the North American Market.
Flexible schedules.
Work from anywhere.
Highly competitive compensation.
seniorSan Francisco, CA, USA
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ОфисLimassol, Cyprus; EU-based employment contract and a 3-year Cyprus work visa with full support for your relocation and visa processes, including assistance for your family; Full relocation package: flights to Limassol for you and your family, a company-covered apartment for the first month, and full relocation support to make your move smooth and hassle-free
seniorLos Angeles, USA
Dublin, Ireland; London, England
УдалённоRemote - United States
seniorChicago
seniorHong Kong, Hong Kong SAR; Singapore, Singapore
ГибридSan Francisco; New York
УдалённоseniorMexico; Colombia; Argentina; Brazil; Costa Rica
Автоотклики