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.}

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.}

About Incode

Incode is the leading provider of world-class identity solutions that is reinventing the way humans authenticate and verify their identities online to power a world of digital trust.

Through our revolutionary identity solutions, we are unleashing the business potential of universal industries including finance, government, retail, hospitality, gaming, and more, by reducing fraud and transforming human interactions with data, products, and services.

We're in the process of rapidly scaling our diverse global team and we're looking for entrepreneurial individuals and leaders who are curious, driven, and excited by ownership to join a Unicorn-status scale-up!

Incode is a Series B unicorn rewriting how the world proves identity. Our AI-powered platform lets leading banks, fintechs, marketplaces, and governments deliver friction-free experiences while defeating fraud and safeguarding privacy. Customers such as Citi, AirBnB, Block, Chime, Sixt, and TikTok rely on Incode to power their identity verification and security.

Recently named a Leader in the Gartner® Magic Quadrant™ for Identity Verification, we're scaling fast — and we're looking for data professionals passionate about investigating data quality problems and building the systems that keep world-class ML models reliable.

The Impact You'll Make

As a Data Analyst on the ID Document Intelligence team, you'll investigate data quality issues, perform root cause analysis, and build the pipelines and automated checks that keep Incode's machine learning ecosystem reliable. You'll ensure that data flows efficiently and accurately through every stage of model training, labeling, and performance tracking.

Your work will be essential to maintaining the scalability, quality, and precision of Incode's document intelligence systems used by millions worldwide.

What You'll Own & Drive

• Root Cause Investigation — Independently investigate data quality issues end-to-end. When a model metric drops or data looks wrong, you own the investigation: forming hypotheses, querying across data sources, and delivering a clear, evidence-backed answer.
• Automated Data Pipelines — Design, build, and maintain pipelines for collection, labeling, validation, and metric computation that support ML training and evaluation.
• Data & Labeling Quality Standards — Establish and monitor consistency checks, accuracy audits, and root-cause analysis when issues impact model outcomes.
• Model Evaluation Metrics — Define, implement, and automate evaluation metrics and reporting that reflect real-world product use cases and business goals.
• Performance Tracking Systems — Build scalable dashboards and monitoring to enable fast, data-driven decisions across teams.
• Workflow Orchestration — Develop and operate reliable orchestration (Airflow, Prefect, or similar) to schedule, observe, and troubleshoot end-to-end pipelines.
• Clean, Maintainable Code — Write SQL and Python to efficiently investigate problems — querying databases, calling internal APIs, and processing data across multiple sources.
• Cross-Functional Partnership — Partner closely with ML engineers, analysts, and product stakeholders to prioritize work by impact, unblock execution, and continuously improve internal tooling for analysis and evaluation.

The Qualities That Set You Apart

• Investigative mindset — You don't stop at the symptom. You chase data anomalies until you find the root cause, and you bring receipts.
• Statistical intuition — You can tell the difference between a meaningful metric shift and noise, and you know how to prove it.
• Builder's bias — You'd rather automate a check than run it manually for the third time.
• Proactive ownership — You spot problems before anyone flags them, and you drive them to resolution without waiting for permission.
• Clear communicator — You translate messy data into crisp answers that ML engineers, PMs, and leadership can act on.

Your Background

• 3+ years of experience as a Data Analyst or in a similar data infrastructure role.
• Strong SQL and Python skills for data investigation and root cause analysis.
• Hands-on experience with AWS Redshift or a similar columnar/cloud database (BigQuery, Snowflake, etc.).
• Solid statistical foundation — you can reason about rates, distributions, significance, and sampling bias.
• Hands-on experience with workflow orchestration tools (Airflow, Prefect, Dagster, etc.).
• Proven experience in data quality management, data preparation, or ML data pipelines.
• A proactive mindset toward identifying problems.
• Strong collaboration and problem-solving skills.
• Background in mathematics, physics, or engineering.

Preferred Experience

• Familiarity with big data technologies or data infrastructure optimization.
• Experience with labeling workflows or ML data preparation pipelines.
• Exposure to AWS or other cloud-based data solutions.
• Interest in machine learning operations (MLOps) and scalable ML systems.

Why Incode?

• Mission with Meaning — Build systems that enable ethical, seamless identity verification for millions.
• Rocket-Ship Growth — Join a company scaling globally with AI at its core.
• Elite Team & Technology — Collaborate with top engineers and data scientists redefining document intelligence.
• Ownership & Autonomy — Operate with end-to-end responsibility for impactful data pipelines.
• Global Impact — Your work will power real-world AI experiences trusted by major enterprises.

Power a world of trust.

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

At JetBrains, code is our passion. Ever since we started, back in 2000, we’ve been striving 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.

Today, AI-powered assistance and agents are becoming a core part of how developers work in our IDEs. The ML Workflows Engineering team is dedicated to removing infrastructure challenges, streamlining machine learning operations (MLOps), and enabling teams to focus on the innovative work that matters most – building impactful ML models and intelligent agents. As part of the team, you'll play a key role in designing tools, automation, and pipelines that make machine learning development seamless and intuitive.

By integrating cutting-edge MLOps practices and engineering excellence, we aim to maximize productivity and remove the complexity of ML infrastructure so that our teams can push the boundaries of what’s possible in AI.

As part of our team, you will:

• Build tools, automation, and workflows to simplify infrastructure-heavy tasks, empowering AI teams to focus on experimentation and solving core challenges.
• Develop robust monitoring, logging, and tracing systems to ensure the performance and reproducibility of ML workflows in production.
• Design, implement, and maintain end-to-end machine learning pipelines to enable the seamless development, training, and deployment of ML models and intelligent agents.
• Work with large-scale distributed systems, including GPU clusters, to support training, fine-tuning, and evaluation of ML models.
• Collaborate with product and development teams to transform high-level goals into concrete, scalable, and maintainable systems.
• Optimize workflows for reproducibility, scalability, and cost-efficiency while keeping ML teams productive and focused on innovation.

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

• Hands-on experience with modern MLOps tooling, including Kubernetes, Cloud providers (GCP and AWS), and ML orchestration frameworks.
• A solid understanding of the ML lifecycle from idea to the customer-facing application.
• The ability to own projects end to end, starting from a high-level problem or product pain point and overseeing it through the design, experimentation, implementation, and iteration phases.
• A customer-centric mindset – you care about how ML engineers are actually working and can translate their needs into actionable, scalable, and maintainable architectural decisions.
• Experience with modern CI/CD systems, like GitHub Actions or JetBrains TeamCity.
• At least three years of Python experience writing clean, maintainable code in modern ML codebases.

Our ideal candidate would have experience with:

• ML orchestrators and workflow tools such as ZenML, Dagster, and Airflow.
• Developing infrastructure components and services using cluster solutions like Kubernetes.
• The development of Python-based backend services.
• Creating and maintaining ML pipelines, including legacy ones.
• Experiment tracking and observability using tools like Weights & Biases, MLflow, Langfuse, or similar.

We’d be especially thrilled if you have experience with: 

• LLM inference frameworks such as vLLM, DeepSpeed, and TensorRT.
• Writing and maintaining Python libraries used by internal (or external) ML engineers.
• A strong theoretical background in NLP and transformer-based approaches.
• Writing code in Java and/or Kotlin.

#LI-HYBRID
#LI-MR1

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.

JetBrains is evolving beyond standalone developer tools toward a unified, AI-native platform for software development.

AI is no longer just an assistant inside the editor – it is becoming an active participant in how software is planned, built, reviewed, and operated across teams and organizations. This shift introduces new challenges that cannot be solved at the level of individual tools alone: governance, security, cost control, observability, and coordinated work between humans and autonomous agents.

Our goal is to build a platform that enables companies to adopt AI in software development in a structured, scalable, and economically efficient manner without locking them into closed ecosystems. This platform will serve as the execution and governance layer for AI-driven development, deeply integrated with developer tools but designed to work across teams, products, and environments.

We are looking for an experienced ML leader who has created products with an ML backbone, weaving together research, technical excellence, and strong product focus.

We are seeking a professional who excels in three key areas: technology, product vision, and business operations. This role involves extensive cooperation with products across the company – both AI-native and just integrating AI.

In this role, you will: 

• Identify, prioritize, and champion high-impact AI projects that align with JetBrains' product strategy and deliver measurable business value.
• Lead a team of about 50 people across multiple AI initiatives, including hiring and developing team leads, ML engineers, and MLOps specialists.
• Set the technical direction for JetBrains’ ML roadmap,  translating cutting-edge AI advancements into practical product innovations.
• Ensure projects deliver on commitments and create measurable value.
• Set technical standards, architectural direction, and best practices for ML development.

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

• The ability to balance long-term R&D with short-term product needs.
• A track record of shipping production ML systems that users actually use.
• Experience building business cases for technical projects.
• A deep understanding of modern ML infrastructure, LLMs, and AI tooling.
• Outstanding stakeholder management skills and are comfortable working with senior leaders.
• The ability to thrive in a fast-paced environment, effectively managing multiple projects simultaneously.
• Excellent management and communication skills.
• Attention to detail in everything you do.

We’d be especially thrilled if you have experience with: 

• Distributed training of multi-billion parameter models.
• CI systems, workflow automation, and experiment tracking.
• The Kotlin programming language.

#LI-KP1 #LI-HYBRID

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.