ZAM Network is a multi-faceted company based in the United States. We specialize in building engaged gaming communities through its three core pillars of marketing, creative services and user research. ZAM operates one of the largest gaming networks in the world including the #1 community for World of Warcraft, Wowhead. 

Wowhead was created with one sole intent: providing World of Warcraft players with tools and information to make their gameplay more enjoyable. All staff members are passionate fans of World of Warcraft, which helps us keep abreast of the most important features other players are interested in! We pride ourselves on our comprehensive database with helpful user comments, popular tools like the Dressing Room and Flying Tracker, lightning-fast datamining to uncover the latest test realm updates, and detailed guides written by professional players on all popular WoW topics including classes, collections, secrets, and raids. We’ve branched out to cover the Diablo franchise and are planning our next stage of growth.

We are currently seeking a Reverse Engineer with extensive data mining experience to join our team as an independent contractor. This is not an entry level role and you will be working to extract both static and runtime game data for World of Warcraft to help Wowhead to expand our current tools to aid our community of gamers. This position is a full-time remote as you will collaborate with the entire Wowhead team as we work together to deliver world-class products to our fans.

Key Responsibilities

• Manage development of the Wowhead Studio application, to facilitate datamined assets of creatures, characters, and other in-game objects
• Extract game data and game assets required to build tools to support our products and services.
• Maintain Wowhead’s model tools using the site’s WebGL model viewers. TypeScript-based standard viewer used in most of Wowhead website.
• Use C++ web assembly-based viewer that is faster with accurate lighting, for various World of Warcraft Player Housing pages.
• Use JavaScript-based Three.js model viewer.
• Maintain comprehensive technical documentation on game data (contents, formats, change history), data mining tools and processes employed, and anything else related to the role.
• Communicate consistently, clearly, and efficiently all assigned task progress, blockers, or any other role-related issues in a prompt and professional manner on a regular basis.

Experience and Technical Requirements

• Previous hands-on experience doing data mining work on World of Warcraft and/or Diablo IV. This is not a “learn as you go” type of role; we operate in a fast paced, highly competitive, and challenging environment.
• Comprehensive understanding using various programming languages (such as C++, Python, C#, TypeScript and JS) in order to choose the best tool for the job.
• Understanding of various debugging, reverse engineering, and custom made tools to accomplish assigned tasks.
• Ability to read and comprehend x86/x64 assembly language, such as via IDA as this role is not solely a “file format” data mining role.
• Strong communication skills in English, both written and verbal, with the ability to convey information clearly and effectively.
• A collaborative mindset; ability to collaborate remotely and coordinate with stakeholders across different time zones.
• Professionalism, reliability, and a commitment to delivering high quality work utilizing your analytical and problem-solving skills.
• Being experienced in Blizzard games will make it easier to understand project requirements and the consumer side.

At JetBrains, code is our passion. Ever since we started back in 2000, we have been striving to make the world’s most robust and effective developer tools. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

We are now building services and agentic tools that provide AI coding agents and end users with deeper context about codebases. Our code retrieval service already delivers meaningful improvements in agent speed and task performance, and we aim to push this further – extracting richer insights than snippets alone at the scale of several hundred thousand repositories. 

We are looking for an AI Engineer who can design and implement agentic tools from scratch, bring them to the end users, and make coding with agents smarter, faster, and more reliable.

In this role, you will:

• Translate product needs into agentic tools and services and ship them to production.
• Scale prototypes to large numbers of users.
• Improve and test our semantic search service.
• Build evaluation pipelines for code retrieval and coding task performance.

We’ll be happy to have you on our team if you have:

• At least five years of hands-on NLP experience.
• Experience in information retrieval systems.
• Strong experience in LLM prompt and tool engineering, as well as with AI agents.
• Solid programming skills in Python and/or Kotlin (and the willingness to learn the language you’re unfamiliar with).
• Experience building and operating production-grade software systems.

We’d be especially thrilled if you have:

• Experience developing in Kotlin or Java.
• Previously worked with code intelligence (e.g. AST, symbol graphs).

#LI-DNI

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning. 

Spectrum collects data from an organization’s code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that’s extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

Spectrum is a resident of JetBrains' startup incubator, with startup speed and autonomy, and backed by 25 years of developer tooling expertise. We are looking for a top-class ML Engineer who will help us shape the future of software development. You will own our AI and ML engineering stack and help define the research agenda for our team. Your technical vision and design decisions will directly shape the product and determine its success.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction, retrieval, and subsequent reasoning.
• Creating the datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving agents for context retrieval, knowledge extraction, and data alignment, which includes prompt engineering, model selection, and inference optimization.
• Establishing MLOps practices, including orchestration, observability, and experiment tracking.
• Collaborating with the engineering team on system design and with JetBrains Research on the research agenda.
• Defining hiring criteria, growing the ML team, and shaping the ML team culture.

We expect you to have:

• A proven track record as an ML/AI Lead.
• At least five years of experience in ML/AI systems, with at least two years focused on LLMs and generative AI.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangChain, LlamaIndex, LangSmith, smolagents, or an equivalent.
• Vector databases and retrieval-augmented generation (RAG) patterns.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal. 

Our ideal candidate would have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• The ability to think strategically about product-led AI, beyond just training models in isolation.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.

#LI-KP1

Software engineers and AI agents alike suffer from the same problem: finding that one person or place that will answer their tough, specific question. Many solutions promise to solve this with similarity search in vector databases. Unfortunately, finding the answer is often a puzzle with pieces to be collected across a myriad of contradictory sources and cannot be solved without surgical search and careful reasoning.

Spectrum collects data from an organization's code, docs, and issues, and organizes knowledge in a unified ontology that AI agents can efficiently search through and reason over. We aim to revolutionize the semantic layer space for software-building organizations and move beyond specs that fall out of sync with code, introducing a living spec – one that's extracted from the whole system and used to keep it aligned. Spectrum is meant to be the single source of truth for all product and architectural knowledge.

A resident of JetBrains' startup incubator, Spectrum enjoys startup speed and autonomy, and is backed by 25 years of developer tooling expertise. We are looking for a Senior AI/ML Engineer to build and evolve the ML-powered systems at the heart of our product.

Your responsibilities will include:

• Designing and building the ML/LLM solution for data ingestion, knowledge extraction and retrieval, and subsequent reasoning.
• Creating datasets, metrics, and pipelines that drive measurable improvements across the system.
• Architecting and improving AI agents, which will involve prompt engineering, model selection, and inference optimization.
• Contributing to our MLOps practices, including orchestration, observability, and experiment tracking.

We expect you to have:

• At least four years of experience building ML/AI systems in production environments, with hands-on LLM experience.
• A deep understanding of the LLM ecosystem, including model architectures and fine-tuning approaches.
• Hands-on experience with:
• Prompt engineering and LLM pipeline design, including evaluation.
• Agentic frameworks such as LangGraph, Pydantic AI, or an equivalent.
• Retrieval-augmented generation (RAG) patterns and vector databases.
• Deploying and scaling LLM-powered applications using APIs (e.g. OpenAI or Anthropic) or open-source models.
• Strong Python skills – Kotlin knowledge would be a plus.
• Excellent communication skills, with the ability to explain complex technical concepts to diverse audiences.
• Proficiency in English, both written and verbal.

Our ideal candidate would also have:

• Experience with ontologies, knowledge graphs, or graph-based reasoning.
• Experience in early-stage startups – you enjoy the zero-to-one phase.
• A background in code analysis, developer tools, or software engineering research.
• Experience with multi-agent systems or complex agentic workflows.
• Actively contributed to relevant open-source projects or publications.

What we offer:

• A competitive salary and JetBrains benefits.
• A generous runway and corporate resources with startup autonomy.
• A motivated team that moves fast, with short feedback loops, rapid prototyping, and lots of ownership.
• Opportunities to publish research at top venues in collaboration with JetBrains Research.

#LI-DNI

Highlights:

Role: Senior ML-Engineer

Location: Serbia, Remote

Language: Russian-speaking team; Strong English required (B2)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to strengthen our ML team. We operate as an internal service and centre of excellence for 10+ product teams at Fundraise Up. This means you won't be tied to a single feature: one day you might be optimising donation amounts and upsell offers, and the next you could be building a smart assistant for the admin panel or working on transaction classification.

We actively use not only classical ML, but also RL, and we're expanding our LLM-based solutions — prompt engineering and pipeline design with LLM APIs (OpenAI and equivalents). That's why we're looking for someone with a broad mindset who isn't afraid to experiment and can choose the most effective approach for each task.

The project's main audience and business team are based in the US. Although the product development team is Russian-speaking, you may occasionally need to write in English.

What You’ll Do

• Develop and deploy ML solutions across different business areas using tabular data (uplift models, recommender systems). We are also actively developing projects that will involve e-commerce mechanics.
• Select the most appropriate ML/LLM approaches or propose alternative solutions.
• Build end-to-end ML solutions: data preparation, training, API development, and monitoring.
• Design prompts and LLM API-based pipelines for specific product tasks: classification, content generation, and response quality evaluation.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting); NLP knowledge is a plus
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (CR, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach to development; we value clean code, knowledge of design patterns, and solid engineering practices
• Data skills: advanced SQL; ability to independently and efficiently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking tools and understanding of production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down problems, choose the right tech stack (or justify a non-ML solution), and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 20 paid vacation days per year
• 15 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Highlights:

Role: Senior ML-Engineer, Finance

Location: Serbia, Remote

Language: Strong English required (C1)

About Us

Fundraise Up is a modern fundraising platform built to make donating to nonprofits as fast and convenient as possible. We continuously innovate to reduce page load times, boost conversion rates, and support a wide range of payment methods. Each month, people around the world contribute tens of millions of dollars through our platform.

The world’s leading nonprofit organizations trust Fundraise Up. UNICEF, the most prominent UN charity, uses our platform for 100% of its online fundraising. So does the American Heart Association, the Alzheimer’s Association, and many others. We’re proud to maintain a 4.9 out of 5 rating on leading review platforms.

We serve the enterprise segment, with a primary client base in the US, Canada, UK, and Australia.

The Team

Our product development team is currently at 150+ and growing. Team members are located across Spain, Serbia, Poland, Portugal, Turkey, Cyprus, Georgia and Armenia. We primarily communicate in Russian.

We’re a tight-knit, high-impact team where every task matters. It’s a dynamic, collaborative environment where smart, curious engineers support one another, share knowledge, and strive for excellence. We encourage open dialogue and host bi-weekly engineering meetups to explore technical topics and showcase team insights.

About the Role

We're looking for an ML Engineer with 5+ years of production experience to own a high-impact client intelligence initiative. Following a successful proof-of-concept with an external consultant, we are bringing this project fully in-house. The ultimate goal is to generate a comprehensive, enriched list of all potential clients globally — understanding their product requirements, industry verticals, and overall revenue potential — and deploy a scoring model that feeds directly into our sales pipeline.

This is an end-to-end ownership role. You will build from the ground up: data collection, enrichment, modeling, and production deployment. The project is co-managed by company executives and has a high strategic value.

What You’ll Do

• Build a market intelligence data-base via collecting different types of data (scraping, enrichment), fixing data pipeline and creating an ML model for scoring and analysis of the raw data.
• Design and operate scrapers to extract key signals from nonprofit websites, including products used, payment tools, and industry vertical indicators.
• Develop critical filters such as an "Is this website for fundraising?" binary classifier, alongside other features that distinguish high-potential prospects.
• Source and integrate financial data from international nonprofit registries, as well as third-party signals from SimilarWeb and Facebook.
• Store and structure the enriched dataset in our internal database, making it accessible and useful across the broader team for research and analysis.
• Work closely with the sales team to understand their qualification criteria. Analyze disqualified accounts in Salesforce to identify common exclusion patterns and refine scoring accordingly.
• Deploy the scoring model and own the process of integrating outputs into Salesforce in a clean, maintainable way.
• Build a scraper to monitor existing clients' websites, tracking whether Fundraise Up tools are correctly implemented across their properties.

Challenges You'll Navigate

• At the scale of ~1 million domains, expect domain duplicates, inconsistent data, and significant noise. You'll need to develop robust, cost-efficient filtering pipelines.
• A single model won't cover everything — you'll likely build several targeted sub-models tailored to specific verticals and geographies as the project matures.
• All of this needs to be accomplished without incurring high infrastructure or data costs. Pragmatic, scrappy solutions are valued here.

Requirements

• 5+ years of ML/DS experience solving real product problems
• Strong expertise in ML and mathematical statistics: solid knowledge of classical algorithms (especially gradient boosting) and understanding of modern NLP/LLM approaches
• Proven experience with large-scale web scraping and data pipeline construction
• Metrics-driven mindset: ability to connect ML metrics (ROC-AUC, F1, RMSE) with business metrics (conversion rate, LTV)
• Strong engineering culture: confident in Python with a product-oriented approach; we value clean code, knowledge of design patterns, and solid engineering practices
• Advanced SQL; ability to independently build complex datasets in ClickHouse and work with MongoDB
• MLOps understanding: hands-on experience with experiment tracking and production workflows (Docker, Git, CI/CD)
• Autonomy: ability to break down ambiguous problems, choose the right tech stack, and deliver to production

Our Tech Stack

Core: Python (uv, ruff), FastAPI, Pydantic, Docker

Models: CatBoost, Uplift Modeling (CausalML), OpenAI (RAG, Prompt-Engineering)

Data: ClickHouse, MongoDB, pandas, Polars, Redis

MLOps: MLflow, Airflow

Monitoring: Grafana, Sentry

Infra: linux server admin, distributed computation

Bonus points

• Curiosity and a hypothesis-driven mindset
• Ability to communicate complex analytical concepts to non-technical audiences
• Detail-oriented with a strong sense of ownership
• Comfort working in fast-paced, data-rich environments

Why work with us

• A strong, collaborative product team that owns what it builds
• Clear product vision and access to real customer feedback from global nonprofit leaders
• Flat structure: no politics, just great work with great people
• Transparent company culture-we share how we’re growing, where revenue comes from, and what’s next
• Long-term focus: we offer equity options and value sustained, meaningful contribution

Benefits

• Private medical insurance for the employee and their family
• 20 paid vacation days per year
• 15 paid public holidays per year
• 5 company-paid sick leave days
• English learning courses
• Relevant professional education
• Gym or swimming pool
• Home Office Setup Assistance: the company offers assistance with purchasing furniture (office chair, office desk, monitor) and other items to create a comfortable workspace
• Co-working
• Remote working

_{**Please note: All official correspondence from Fundraise Up will exclusively originate from the @fundraiseup.com domain. Exercise caution and ensure the authenticity of emails claiming to be from our company.}

Gambling.com Group (Nasdaq: GAMB) is a multi-award winning provider of marketing and sports data services looking for exceptional talent interested in the fast-paced, high-growth online gambling industry. The company operates a portfolio of renowned websites and brands – including flagship site Gambling.com and sports betting site Bookies.com as well as iGaming-focused sites Casinos.com, BonusFinder.com and Freebets.com.

In addition to its marketing operations, Gambling.com Group provides sports data services through consumer subscription platforms like OddsJam and RotoWire, along with B2B services through OpticOdds. These offerings deliver real-time data, actionable insights, and technology driven tools to both consumers and enterprise partners.

As the first and only online gambling affiliate publicly traded in the U.S., Gambling.com Group has earned recognition as a leader in its field – most recently winning Affiliate of the Year at the 2025 EGR Operator Awards.

Are you ready to take the next step in your career?

Functions and Scope

This is an AI engineering role embedded in a commercial function. The primary output of this role is agents and automated workflows — built, owned, and iterated on by you. Commercial knowledge informs what gets built. The building is the job.

Commercial Operations & Optimisation

• Support the commercial function in commercially optimising vertical site performance to drive revenue across all channels — doing so primarily by identifying where AI agents and automated workflows can replace or accelerate manual commercial processes, and then building them.
• Act as the primary operational owner of commercial operational processes across all verticals,which in practice means owning the AI and automation layer that powers those processes, not just the processes themselves.
• Conduct ongoing competitor analysis, develop new commercial process and agentic workflow ideas, and collaborate with product and marketing teams to drive operational improvements,using AI tooling to run analysis at scale, generate workflow concepts, and prototype solutions faster than traditional approaches allow.
• Collaborate with commercial leadership to set, manage, and monitor BAU processes, KPIs, and OKRs across the commercial operations function,building AI-assisted reporting and monitoring infrastructure so that performance visibility is automated, not manual.
• Leverage AI to enhance internal software and tooling to build effective, transparent internal processes across commercial operations,this is not a peripheral responsibility, it is the core mechanism through which this role delivers value. You are expected to be actively building, not just recommending.

Workflow Architecture & Process Design

• Identify inefficiencies and bottlenecks across commercial operations and design structured solutions,your default answer to an inefficiency is an agent or an automated workflow, with manual process redesign as the fallback where automation is not yet viable.
• Own the design and deployment of operational workflows that reduce manual effort and improve output quality and consistency across the commercial team ,from initial architecture through to live deployment, with measurable reduction in human effort as the success metric.
• Develop and maintain playbooks and performance standards for all commercial workflows, including documentation of how each AI agent or automated workflow is expected to behave, what good output looks like, and where human review is required.
• Coordinate with sales and commercial leadership on operational prioritisation and workflow sequencing,translating commercial priorities into a build roadmap for agents and automations, and managing that roadmap actively.

Agent & Automation Development

This is the core of the role. You will be building AI agents. Not scoping them for others to build, not advising on them, not reviewing them after the fact — designing, building, deploying, and iterating on them yourself, end to end. If you have not built and shipped an AI agent in a professional context, this role is not the right fit.

• Lead the identification and scoping of agentic automation opportunities across commercial operations,this means proactively finding problems worth solving with AI, not waiting to be briefed. You are expected to surface opportunities, make the case for them, and own the build.
• Own and build the full development lifecycle for commercial agents across all commercial operations,from problem definition and workflow brief through to prompt architecture, tool integration, testing, deployment, and post-launch iteration. You are the builder, not the commissioner.
• Ensure quality, accuracy, and commercial alignment of all automated outputs, establishing QA standards and performance benchmarks for every agent you deploy, and holding yourself accountable for what those agents produce at scale.
• Iterate on agent performance post-deployment based on commercial data, stakeholder feedback, and operational signals,treating deployed agents as live products that require ongoing maintenance and improvement, not finished projects.

Quality Assurance & Reporting

• Establish and oversee QA processes across all commercial operations workflows,including designing the human review layer that sits alongside AI-driven outputs, defining what requires sign-off before going live, and building the infrastructure to enforce that consistently.
• Generate, analyse, and present operational KPI reports to senior stakeholders,using AI-assisted tooling to automate data aggregation and surface anomalies, so that your contribution at the reporting layer is insight and recommendation, not manual data pulling.
• Monitor workflow and agent performance, surfacing actionable recommendations to commercial leadership on a regular basis, including honest assessment of where agents are underperforming, where outputs are drifting from expected standards, and what needs to be rebuilt or retired.
• Operate as the internal expert on AI-enabled tools including Claude, Lovable, and others,not as a power user, but as the person who understands these platforms deeply enough to build production-grade commercial workflows on top of them, apply rigorous judgement to their outputs, and teach others how to work alongside them effectively.

Key requirements

Essential experience

• Experience in a commercial operations, revenue operations, or similar ops role,ideally within a digital media, affiliate, or multi-vertical online business
• You have built AI agents and shipped them into a live production environment,this is the baseline requirement for this role, not an aspiration. If your experience is limited to using AI tools, prompting chatbots, or working within workflows someone else built, this role is likely beyond where you are right now
• Demonstrable, end-to-end ownership of the agent development lifecycle, from identifying the commercial problem, writing the workflow brief, designing the prompt architecture, integrating tools, testing, deploying, and iterating post-launch. You were the builder, not the person who commissioned or reviewed someone else's build
• Experience with AI platforms and tools such as Claude, Lovable, n8n, or equivalent, with specific, named examples of what you built on them, what it did, and how you measured whether it was working
• Track record of designing and documenting operational processes, playbooks, and performance standards,including documentation of how agents are expected to behave, what good output looks like, and where human review is required
• Experience establishing QA frameworks for AI-generated or automated outputs, setting performance benchmarks, monitoring for drift or failure, and iterating on agent behaviour based on real-world results
• Comfortable owning and reporting on KPIs and OKRs, with experience building automated reporting infrastructure rather than pulling data manually

You must be able to demonstrate, with specific examples, that you have:

• Built and deployed at least one AI agent in a professional context and can walk through exactly what it did, how you built it, where it failed, and what you did to fix it
• Designed prompt architecture for a production workflow,not just written prompts, but structured them as part of a repeatable, scalable agent build
• Integrated AI agents with external tools, platforms, or data sources as part of a live commercial or operational workflow
• Identified a commercial or operational problem, translated it into an agent build brief, built the solution yourself, and measured the outcome
• Established and enforced QA standards for automated outputs, including defining what human review is required and building the process to ensure it happens consistently
• Iterated on a deployed agent based on performance data or stakeholder feedback, treating it as a live product, not a finished project

Candidates who cannot provide concrete, specific examples of building and shipping agents will not progress past the application stage. This is a builder role,your portfolio of what you have built is the application.

Skills & capabilities

• Prompt architecture and agent design,able to structure AI instructions for production-grade reliability, not just one-off outputs
• Tool integration,comfortable connecting AI agents to external platforms, APIs, data sources, and internal tooling as part of a live workflow build
• Commercial judgement,able to prioritise build decisions based on revenue impact and business context, identifying which automation opportunities are worth the investment
• Process design instinct,able to map a commercial problem, identify the automation opportunity within it, and design a structured agent-based solution
• Strong cross-functional communication,able to translate between commercial stakeholders who define the problem and technical counterparts who support the infrastructure
• Rigorous approach to AI output review ,understanding that what an agent produces at scale is your responsibility, and building QA into every deployment accordingly

Behaviours we're looking for

• You have shipped things,your instinct is to build a working version, get it into a live environment, and improve it from there rather than designing indefinitely
• You treat deployed agents as live products,you monitor them, catch when they drift, and fix them without being asked
• You apply structured commercial thinking to what you build,you're not building for technical elegance, you're building to remove manual effort and drive revenue outcomes
• You are honest about the limits of what you've built,you know where your agents are reliable and where they require human oversight, and you design for that honestly
• You communicate proactively with commercial leadership when something isn't working, an underperforming agent that goes unreported is a failure of this role, not just a technical issue

Nice to have

• Experience in the affiliate, igaming, media, or performance marketing sectors
• Familiarity with competitor analysis methodologies in a commercial context
• Exposure to product or engineering teams in a workflow or tooling capacity
• Experience building agents that operate across multiple tools or platforms simultaneously,multi-step, multi-tool agent architectures rather than single-task automations

A note for applicants: If your experience with AI is limited to using consumer tools, prompting chatbots, or working within workflows someone else built, this role is likely a step beyond where you are right now. We are looking for someone who has built agents, shipped them into a live environment, watched them fail, fixed them, and made them better. That experience is the baseline, not the ceiling

Perks & Benefits

• Comprehensive private Healthcare Insurance
• Flexible work environment and home office available
• Home office allowance
• Gym & Leisure Allowance
• All the hardware and software you need to be successful
• Regular company events and social outings, activities, Spot Awards and a Monthly Social Club
• Access to courses for Personal and Career Development
• Company Paid Volunteer Day

At JetBrains, code is our passion. Ever since we started, back in 2000, we have strived to make the strongest, most effective developer tools on earth. By automating routine checks and corrections, our tools speed up production, freeing developers to grow, discover, and create.

AI features in JetBrains IDEs, developed by the IntelliJ AI team, have quickly become a core part of how developers work inside our IDEs. The IntelliJ AI team partners with product groups across JetBrains to embed advanced AI features that accelerate developer workflows and deliver real value to software engineers.

We are currently looking to hire a Senior Machine Learning Engineer to help us realize our ambitious vision of creating AI assistance that supports the entire development lifecycle across JetBrains IDEs. If selected, you will join the ML subteam within IntelliJ AI, driving the development of our ML system from end to end by defining evaluation and metrics, shaping context orchestration, and helping product teams tailor AI capabilities to their needs.

In this role, you will:

• Design and drive evaluation frameworks for AI features, including metrics, experiments, and agent trace analysis.
• Diagnose model performance issues (e.g. prompt drift, context mismatches, and latency/quality trade-offs) and translate findings into actionable improvements.
• Experiment with contexts and lightweight models to continuously develop our ML system.
• Act as the ML liaison for product teams across JetBrains, adapting and scaling AI capabilities in JetBrains IDEs to their needs.
• Build and maintain small helper models (e.g. re-rankers, classifiers, embedding models) to support domain-specific tasks.
• Collaborate with colleagues in ML, product, engineering, and analytic teams to deliver improvements and monitor their impact in production.
• Stay up to date with research in the fields of LLMs, agents, and evaluation, bringing best practices into our workflows.
• Mentor junior engineers and help shape team culture, processes, and tooling around experimentation and evaluation.

We’d be happy to have you on our team if you: 

• Have 5+ years of experience as an ML Engineer, with a solid background in production-grade ML systems (especially LLMs and agent architectures).
• Have experience with LLM evaluation methods and frameworks.
• Can design and run end-to-end experiments – hypotheses, metrics, data collection (including traces/logs), analysis, and decision-making.
• Are skilled in context-aware pipelines or conversational/agent systems.
• Have strong Python programming skills.
• Bring hands-on experience in fine-tuning or training smaller models (e.g. domain-specific fine-tuning and lightweight customizations).
• Communicate clearly and effectively across teams, translating ML/AI insights into product features.
• Have prior mentorship experience with ML/evaluation engineers.
• Thrive in a cross-functional, fast-moving environment, taking ownership, iterating quickly, and delivering results.

We’d be especially thrilled if you have: 

• Familiarity with agent-based systems and orchestrating multi-step reasoning agents.
• Experience with the Kotlin programming language.

#LI-MR1

Our Machine Learning teams build with the latest tools and launch for Silicon Valley startups and Life Science giants alike.

Join our team to work remotely, ship projects you’re proud be a part of, and enjoy every other Friday off (yes, we really take it 😎)

The Role

• Understanding of statistical, ML and deep learning algorithms
• Analyze errors of models and design strategies to overcome them
• Deploy, maintain, and upgrade ML models and pipelines
• Ambition to learn and grow into different industries with a modern tech stack
• Autonomy, adaptability and positivity (fully remote and globally distributed team)

The Required Hard Skills

• Bachelor's Degree in Computer Science or related
• 2+ years of ML engineering experience
• Experience with Python, ML libraries and AI/ML frameworks (PyTorch, HuggingFace, TensorFlow, etc.)

• Excellent English - Being a global team, we work entirely in English for meetings, customer calls and business communications
• CV written in English

Bonus Points for Experience with…

• Building GenAI solutions, namely prompt engineering (e.g: Langchain), fine-tuning and serving LLMs, search and embeddings, etc.
• MLOps, favorably in AWS (e.g: Sagemaker) as well as standards tools (e.g: MLFlow)
• Visualizing and manipulating big datasets
• NLP

The Required Soft Skills

• Curiosity—Ambition to learn and grow into different industries with a modern tech stack
• Autonomy and positivity—We’re a fully remote, globally distributed team
• Teamwork—Enjoy a collaborative approach
• Adaptability—Operate with a startup mindset and move at a startup pace

The Benefits

• Every other Friday off (26 extra days off a year)
• Remote and flexible
• Explore and Relocation programs (three months work abroad or full international relo)
• Paid sick days and local holidays
• Business English classes program
• Continuous Learning Support
• Fitness and/or Mental Health Subscriptions
• Access to LokaLabs™, our internal research and development program
• Defined career path

Our Machine Learning teams build with the latest tools and launch for Silicon Valley startups and Life Science giants alike.

Join our team to work remotely, ship projects you’re proud be a part of, and enjoy every other Friday off (yes, we really take it 😎)

The Role

• Understanding of statistical, ML and deep learning algorithms
• Analyze errors of models and design strategies to overcome them
• Deploy, maintain, and upgrade ML models and pipelines
• Ambition to learn and grow into different industries with a modern tech stack
• Autonomy, adaptability and positivity (fully remote and globally distributed team)

The Required Hard Skills

• Bachelor's Degree in Computer Science or related
• 2+ years of ML engineering experience
• Experience with Python, ML libraries and AI/ML frameworks (PyTorch, HuggingFace, TensorFlow, etc.)

• Excellent English - Being a global team, we work entirely in English for meetings, customer calls and business communications
• CV written in English

Bonus Points for Experience with…

• Building GenAI solutions, namely prompt engineering (e.g: Langchain), fine-tuning and serving LLMs, search and embeddings, etc.
• MLOps, favorably in AWS (e.g: Sagemaker) as well as standards tools (e.g: MLFlow)
• Visualizing and manipulating big datasets
• NLP

The Required Soft Skills

• Curiosity—Ambition to learn and grow into different industries with a modern tech stack
• Autonomy and positivity—We’re a fully remote, globally distributed team
• Teamwork—Enjoy a collaborative approach
• Adaptability—Operate with a startup mindset and move at a startup pace

The Benefits

• Every other Friday off (26 extra days off a year)
• Remote and flexible
• Explore and Relocation programs (three months work abroad or full international relo)
• Paid sick days and local holidays
• Business English classes program
• Continuous Learning Support
• Fitness and/or Mental Health Subscriptions
• Access to LokaLabs™, our internal research and development program
• Defined career path

Years from now, history will look back at this moment as a landmark for the human race—the moment when generative artificial intelligence began to change everything. Luckily, you happen to be living through it. Now what? 

If you’re one of those rare people driven to add their intellectual energy to the relentless momentum of technological advancement, consider Loka your optimal leverage point. 

Loka, a globally distributed tech consultancy based in Silicon Valley, is seeking a Senior Machine Learning Engineer to join our growing team. In this position you will serve as the primary specialist in designing and implementing machine learning solutions across multiple projects. Your expertise in ML algorithms and ML, DL and Foundation Models will empower us to develop robust, scalable systems and improve them over time. Ultimately we expect you to not just fit in with our ML crew but to elevate it to new heights. 

Our technical teams help clients launch innovations that fix the climate, defeat cancer, improve agricultural efficiencies, teach kids to read and more. We work with all kinds of companies, from Silicon Valley startups to major household brands, always guided by our fundamental belief that mission matters. 

We count more than 100 certified specialists, technical experts and PhDs among our teammates—committed Lokals who contribute to their brilliance not only to serving our clients but to mentoring junior colleagues as well. We work entirely remotely, test new ideas with an in-house incubator called LokaLabs, observe local holidays and take every other Friday off (really). We’re as proud of our culture as we are of our projects. You will be too. 

The Role

• Take full responsibility for assigned tasks and projects, ensuring accountability for outcomes and results.
• Understand business objectives and develop models that help achieve them, along with metrics to track progress.
• Design and implement complex ML systems using classical machine learning, deep learning and foundation models, adhering to best practices.
• Lead client communications by gathering requirements, managing expectations and communicating deliverables effectively.
• Wrangle, explore and visualize data with a keen eye for issues requiring data cleaning, as well as differences in data distribution that may affect post-deployment performance.
• Analyze model errors and design strategies to overcome them.
• Deploy, maintain and upgrade ML models and pipelines.
• Follow Loka’s career track for growth by demonstrating technical excellence, innovation, autonomy, ownership, communication and teamwork.
• Drive architectural decisions and contribute to high-level planning and strategy. 
• Direct report to ML leads.
• Stay updated with industry trends to incorporate cutting-edge techniques and tools into projects.
• Write and maintain technical documentation.
• Provide guidance and mentorship to junior ML engineers within the team.
• Collaborate cross-functionally with other teams (Data Engineering, DevOps, Backend) to ensure seamless integration of ML solutions.
• Continuously optimize models for performance, scalability and cost-effectiveness, especially within the AWS environment.

Required Hard Skills 

• 4+ years of AI/ML engineering experience
• Bachelor’s degree in Computer Science or related
• Experience with Python, ML libraries and AI/ML frameworks (sklearn, PyTorch, HuggingFace, TensorFlow, Transformers, LangChain/LangGraph, Llamlndex, smolagents, strands-agents etc.) 
• Experience building GenAI solutions through prompt engineering, fine-tuning and developing agents with common patterns like Agentic RAG, NLQ etc.
• Client-facing experience
• Familiarity with containerization and orchestration tools 

Additional Requirements 

• Excellent English - Being a global team, we work entirely in English for meetings, customer calls and business communications
• CV sent in English

Not Required but Nice to Have

• Experience with MLOps/LLMOps, preferably in AWS (e.g: Sagemaker/Bedrock), as well as standards tools (e.g. MLFlow, LangFuse) 
• Experience in consultancy environments or startups, including working directly with clients, managing projects and adapting to different settings. - Plus

Required Soft Skills 

• Curiosity: Strive to learn and grow into different industries with a modern tech stack. 
• Autonomy and positivity: We’re a fully remote, globally distributed team. 
• Teamwork: Enjoy a collaborative approach. 
• Adaptability: Operate with a startup mindset and move at a startup pace. 

Benefits

• Every other Friday off (26 extra days off a year)
• Remote-first culture
• Explore and Relocation programs (three months work abroad or full international relo)
• Paid sick days and local holidays
• Business English classes program
• Continuous Learning Support
• Fitness and/or Mental Health Subscriptions
• Access to LokaLabs™, our internal research and development program
• Defined career path

Your achievements matter to us! Ensure your CV and LinkedIn and GitHub profiles are up to date and accurately reflect your experience. 

Years from now, history will look back at this moment as a landmark for the human race—the moment when generative artificial intelligence began to change everything. Luckily, you happen to be living through it. Now what? 

If you’re one of those rare people driven to add their intellectual energy to the relentless momentum of technological advancement, consider Loka your optimal leverage point. 

Loka, a globally distributed tech consultancy based in Silicon Valley, is seeking a Senior Machine Learning Engineer to join our growing team. In this position you will serve as the primary specialist in designing and implementing machine learning solutions across multiple projects. Your expertise in ML algorithms and ML, DL and Foundation Models will empower us to develop robust, scalable systems and improve them over time. Ultimately we expect you to not just fit in with our ML crew but to elevate it to new heights. 

Our technical teams help clients launch innovations that fix the climate, defeat cancer, improve agricultural efficiencies, teach kids to read and more. We work with all kinds of companies, from Silicon Valley startups to major household brands, always guided by our fundamental belief that mission matters. 

We count more than 100 certified specialists, technical experts and PhDs among our teammates—committed Lokals who contribute to their brilliance not only to serving our clients but to mentoring junior colleagues as well. We work entirely remotely, test new ideas with an in-house incubator called LokaLabs, observe local holidays and take every other Friday off (really). We’re as proud of our culture as we are of our projects. You will be too. 

The Role

• Take full responsibility for assigned tasks and projects, ensuring accountability for outcomes and results.
• Understand business objectives and develop models that help achieve them, along with metrics to track progress.
• Design and implement complex ML systems using classical machine learning, deep learning and foundation models, adhering to best practices.
• Lead client communications by gathering requirements, managing expectations and communicating deliverables effectively.
• Wrangle, explore and visualize data with a keen eye for issues requiring data cleaning, as well as differences in data distribution that may affect post-deployment performance.
• Analyze model errors and design strategies to overcome them.
• Deploy, maintain and upgrade ML models and pipelines.
• Follow Loka’s career track for growth by demonstrating technical excellence, innovation, autonomy, ownership, communication and teamwork.
• Drive architectural decisions and contribute to high-level planning and strategy. 
• Direct report to ML leads.
• Stay updated with industry trends to incorporate cutting-edge techniques and tools into projects.
• Write and maintain technical documentation.
• Provide guidance and mentorship to junior ML engineers within the team.
• Collaborate cross-functionally with other teams (Data Engineering, DevOps, Backend) to ensure seamless integration of ML solutions.
• Continuously optimize models for performance, scalability and cost-effectiveness, especially within the AWS environment.

Required Hard Skills 

• 4+ years of AI/ML engineering experience
• Bachelor’s degree in Computer Science or related
• Experience with Python, ML libraries and AI/ML frameworks (sklearn, PyTorch, HuggingFace, TensorFlow, Transformers, LangChain/LangGraph, Llamlndex, smolagents, strands-agents etc.) 
• Experience building GenAI solutions through prompt engineering, fine-tuning and developing agents with common patterns like Agentic RAG, NLQ etc.
• Client-facing experience
• Familiarity with containerization and orchestration tools 

Additional Requirements 

• Excellent English - Being a global team, we work entirely in English for meetings, customer calls and business communications
• CV sent in English

Not Required but Nice to Have

• Experience with MLOps/LLMOps, preferably in AWS (e.g: Sagemaker/Bedrock), as well as standards tools (e.g. MLFlow, LangFuse) 
• Experience in consultancy environments or startups, including working directly with clients, managing projects and adapting to different settings. - Plus

Required Soft Skills 

• Curiosity: Strive to learn and grow into different industries with a modern tech stack. 
• Autonomy and positivity: We’re a fully remote, globally distributed team. 
• Teamwork: Enjoy a collaborative approach. 
• Adaptability: Operate with a startup mindset and move at a startup pace. 

Benefits

• Every other Friday off (26 extra days off a year)
• Remote-first culture
• Explore and Relocation programs (three months work abroad or full international relo)
• Paid sick days and local holidays
• Business English classes program
• Continuous Learning Support
• Fitness and/or Mental Health Subscriptions
• Access to LokaLabs™, our internal research and development program
• Defined career path

Your achievements matter to us! Ensure your CV and LinkedIn and GitHub profiles are up to date and accurately reflect your experience.