PyTorch Jobs in Portugal.
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Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
Cision has one of the largest media and content databases on Earth. Our data science team works on building intelligent and high-impact features driven by machine learning and NLP.
As a Staff Data Scientist, you will be part of our Machine Learning and Data Science team that build and deploy machine learning models used directly in our products. You will work on complex, high-visibility problems and collaborate closely with engineering, product, and analytics teams to turn prototypes into production-grade solutions.
This role is ideal for someone who operates with strong ownership, delivers high-quality work at pace, and acts as a subject-matter expert on key ML components or services.
Key Responsibilities
Develop and deliver complex machine learning and NLP solutions end-to-end.
Analyze large datasets to uncover insights, design features, and guide modeling decisions.
Build, test, and deploy ML models into production systems in partnership with engineering teams.
Work independently to create tools, frameworks, and reusable components that accelerate model development.
Collaborate cross-functionally with product managers, engineers, and analysts to translate prototypes into production-grade models and services.
Demonstrate sound judgment around risk, workload management, prioritization, and escalation.
Act as a go-to SME for your domain and contribute significantly to team commitments and delivery.
Required Qualifications
8+ years of professional experience in a software or ML engineering environment.
5+ years applying advanced statistical or machine learning techniques to real-world business problems.
Advanced degree in a quantitative field (e.g., Statistics, Mathematics, Economics, Computer Science, Machine Learning) or equivalent practical experience.
Proven track record of delivering ML solutions used in production.
Strong proficiency with Python and ML-focused libraries such as Pandas, NumPy, scikit-learn, TensorFlow, or PyTorch.
Hands-on experience with cloud-based ML workflows in GCP and/or AWS (Kubernetes, Nvidia Triton, Vertex AI, Sagemaker, and similar tools)
Proficiency with database query languages (QL) and experience working with large-scale datasets.
Ability to clearly communicate complex technical concepts to non-technical audiences.
Strong sense of ownership, accountability, and commitment to quality.
Preferred Qualifications
Experience with modern NLP techniques and pretrained model ecosystems.
Experience building scalable data pipelines or model-serving architectures.
Familiarity with MLOps concepts and practices.
Experience in building production-quality and scalable inf inerence systems with Python, Java, or general-purpose languages.
What Your Day-to-Day Might Look Like
Experimenting with various modeling techniques using GCP Vertex AI or AWS SageMaker.
Analyzing model performance and implementing strategies to improve accuracy, robustness, and reliability.
Designing and engineering new features based on exploratory data analysis.
Identifying, evaluating, and adapting open-source models to solve NLP and ML tasks.
Partnering with engineers to optimize ML models for deployment and monitoring.
Ready to apply?
Apply to Cision
About Smartcat
Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises.
We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one.
Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale.
Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us.
Join us in unlocking global potential, one human and agent team at a time.
Mission
As a AI Translation Engineer, you will be at the forefront of advancing our platform’s translation capabilities. Leveraging your expertise in machine learning including applied research, fine tuning, benchmarking, and inference optimization, you will deliver high-performance solutions that power critical features for our growing client base.
Requirements
- Evaluation engineering: Translates product features into measurable user use cases; selects a small set of reliable offline metrics; builds benchmarks and runs slice analysis across languages and domains; designs rubrics and reference-less MT evaluation for ambiguous cases; defines online metrics and guardrails, runs A/B tests and staged rollouts, and validates that offline gains translate into production impact while spotting metric loopholes and regressions
- Data fluency: Owns end-to-end dataset pipelines: multi-source ingestion → cleaning/validation → scalable multilingual datasets, with versioning and auditability
- Classical NLP foundations: Understands MT/search text normalization and core matching approaches (exact/fuzzy, typo tolerance, multi-word + overlap handling, tries/Aho–Corasick/inverted index basics), and applies them to improve preprocessing and retrieval
- LLM operations: Operates external LLM providers end-to-end: designs prompts for structured generation/evaluation; builds automated filters/validators; generates synthetic data at scale using self-consistency and multi-provider “consilium”; selects and routes across providers based on quality–latency–cost; and uses self-hosted models when helpful for quality analysis/judging and provider fine-tuning data prep
- Practical production engineering: Can write lightweight services/jobs when needed and ship them with structured logs, monitoring/alerts, reliability basics (retries, idempotency, fallbacks), and scalability considerations; collaborates effectively with Dev/Platform
Key Responsibilities
- Develop and improve benchmarks for translation problems
- Work with NER, word alignment, automatic translation quality scoring system, and other problems
- Set up infrastructure for self-hosted solutions
Our technologies
- ML/Backend: Python, C#, PyTorch, Transformers
- DB: MongoDB, PostgreSQL, Elasticsearch
- Messaging: Apache Kafka
- Cloud: Amazon AWS
- Monitoring: ELK, Prometheus, Grafana
Why joining Smartcat might be your best move so far
- A global, connected team
We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. - Be part of an AI Native Organization
We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. - Innovating a $100 Billion industry
Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. - Join the rocketship to scale-up 10x and beyond together
We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. - Smartcat Culture Code: Where Diversity Meets High Performance
At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment..png)
Ready to apply?
Apply to Smartcat
About Smartcat
Smartcat is building the future of work, where human expertise meets digital teammates to drive 10x to 1000x productivity gains for the world’s leading enterprises.
We’re on the frontier of an entirely new category: Agentic AI. We enable enterprises to build high-performing hybrid workforces made up of both humans and AI agents. These AI agents aren’t generic copilots. They’re fully trained digital teammates that learn from your best people, your content, and your business strategy—ready to get to work from day one.
Our platform combines generative AI, human-in-the-loop workflows, and a living Enterprise Skill Graph that continuously learns and improves. Whether you're launching a product globally, onboarding new hires, translating learning content, or aligning legal teams across regions, Smartcat turns knowledge into action and action into scale.
Over 1,000 companies, including 20% of the Fortune 500, rely on Smartcat to bring their business to the world—instantly, accurately, and in every language. As a Series C company with consistently high year-over-year growth, we’re scaling fast and investing in people who want to shape the future of work with us.
Join us in unlocking global potential, one human and agent team at a time.
Mission
As a AI Translation Engineer, you will be at the forefront of advancing our platform’s translation capabilities. Leveraging your expertise in machine learning including applied research, fine tuning, benchmarking, and inference optimization, you will deliver high-performance solutions that power critical features for our growing client base.
Requirements
- Evaluation engineering: Translates product features into measurable user use cases; selects a small set of reliable offline metrics; builds benchmarks and runs slice analysis across languages and domains; designs rubrics and reference-less MT evaluation for ambiguous cases; defines online metrics and guardrails, runs A/B tests and staged rollouts, and validates that offline gains translate into production impact while spotting metric loopholes and regressions
- Data fluency: Owns end-to-end dataset pipelines: multi-source ingestion → cleaning/validation → scalable multilingual datasets, with versioning and auditability
- Classical NLP foundations: Understands MT/search text normalization and core matching approaches (exact/fuzzy, typo tolerance, multi-word + overlap handling, tries/Aho–Corasick/inverted index basics), and applies them to improve preprocessing and retrieval
- LLM operations: Operates external LLM providers end-to-end: designs prompts for structured generation/evaluation; builds automated filters/validators; generates synthetic data at scale using self-consistency and multi-provider “consilium”; selects and routes across providers based on quality–latency–cost; and uses self-hosted models when helpful for quality analysis/judging and provider fine-tuning data prep
- Practical production engineering: Can write lightweight services/jobs when needed and ship them with structured logs, monitoring/alerts, reliability basics (retries, idempotency, fallbacks), and scalability considerations; collaborates effectively with Dev/Platform
Key Responsibilities
- Develop and improve benchmarks for translation problems
- Work with NER, word alignment, automatic translation quality scoring system, and other problems
- Set up infrastructure for self-hosted solutions
Our technologies
- ML/Backend: Python, C#, PyTorch, Transformers
- DB: MongoDB, PostgreSQL, Elasticsearch
- Messaging: Apache Kafka
- Cloud: Amazon AWS
- Monitoring: ELK, Prometheus, Grafana
Why joining Smartcat might be your best move so far
- A global, connected team
We’re a team of 200+ people across 30+ countries, working together through a hub-and-spoke model anchored in eight key locations: New York, London, Lisbon, Costa Rica, Serbia, Armenia, Georgia, and Spain. Most of our roles are remote-friendly, giving you the flexibility to do your best work from where you thrive. For customer-facing teams, we prioritize proximity to our customers, ensuring we stay deeply connected to their needs and deliver an exceptional experience. No matter where you’re based, you’ll be part of a highly collaborative, globally-distributed team that values ownership, speed, and meaningful impact. - Be part of an AI Native Organization
We are highly innovative, using AI across all areas of the organization to accelerate decision-making and free people to focus on strategy and high-impact work. We embrace new ideas and encourage all Smartcaters, regardless of level or department, to manage their own AI Agents. At Smartcat you’ll shape how AI transforms the workplace and play an integral role in ensuring Smartcat remains a leader in AI innovation. - Innovating a $100 Billion industry
Smartcat is reshaping the $100B multilingual content industry with an AI-powered platform that makes it easy for companies to create, translate, and localize global content at scale. Our platform enables enterprise teams to move away from slow, traditional outsourcing methods, and achieve fast, high-quality results, at a fraction of the cost. - Join the rocketship to scale-up 10x and beyond together
We are looking for someone to become an integral part of our team and play a crucial role in the most exciting part of our journey: transitioning from a post-Series C startup to a company exceeding $100M in ARR and $1B in valuation. Our journey isn’t for the faint of heart. We are growing at 130% YoY, thanks to our strong product-market fit and high-performing team, and plan to accelerate from here. - Smartcat Culture Code: Where Diversity Meets High Performance
At Smartcat, we are committed to building a culture that highlights respect and appreciation for each individual's unique background and perspective, while maintaining a strong focus on results and engagement. We believe in welcoming everyone and fostering an inclusive environment where team members can be their authentic selves at work. Our commitment to inclusion is steadfast, and we stand firmly against discrimination and harassment.
Ready to apply?
Apply to Smartcat
Senior Data Scientist
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We're a leading SaaS provider revolutionising how fintech companies navigate complex regulatory landscapes. Our platform powers compliance and risk management for hundreds of innovative financial services companies, from emerging startups to established enterprises. We believe in empowering our teams to solve meaningful problems and create exceptional value for our customers.
Role Summary
As a Senior Data Scientist at ComplyAdvantage, you will lead the development and refinement of sophisticated data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, where you will spend 80% of your time conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value over 3-6 month horizons. In addition to driving deep-dive R&D, you will provide expert advisory support and technical leadership to Product and Engineering teams. By leading AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features while mentoring more junior members of the tribe.
Key Responsibilities
- Lead R&D in GenAI and Agentic AI: Design and prototype high-impact, novel solutions for financial crime detection, focusing on multi-agent systems and RAG architectures built on foundational LLM frameworks.
- Drive Production Excellence: Partner with Engineering and Product leadership to architect and oversee the integration of AI components into core product features. You will define the standards for reliability, scalability, and ethical AI performance, ensuring research prototypes transition into robust, production-grade solutions.
- Establish Evaluation Frameworks: Lead the development of robust evaluation methodologies for LLM and agentic AI systems, defining industry-standard metrics for task completion, reasoning accuracy, and system reliability.
- Evaluate Model Context Protocol (MCP): Research applications to connect our AI systems with external data sources and tools, providing strategic recommendations for engineering implementation.
- Strategic Data Insights: Conduct advanced exploratory analysis across multiple data sources to uncover insights that directly influence product development decisions and agent behavior.
- Research & Innovation: Continuously research and evaluate emerging tools and best practices in data science and Agentic AI to keep ComplyAdvantage at the forefront of the field.
- Technical Leadership & Mentoring: Engage across multi-disciplinary teams to share expertise, perform code reviews, and provide career development support to junior data scientists.
Required Qualifications
- MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
- 4-7 years of professional experience in data science or machine learning, with a demonstrable impact on production systems.
- Expert-level proficiency in Python, including the core data science ecosystem such as Pandas, NumPy, and Scikit-learn.
- Deep experience with modern ML frameworks (e.g., TensorFlow, PyTorch) for advanced research and prototyping.
- Strong expertise in Agentic AI and LLMs: Advanced knowledge of agentic AI frameworks (e.g., LangChain, Pydantic AI) and experience optimising retrieval systems like RAG.
- Experience with Distributed Computing: Practical knowledge of platforms like Spark or Dask for large-scale data analysis.
- Technical Leadership: Proven track record of leading technical research projects with successful production outcomes and communicating complex concepts to diverse audiences.
Preferred Qualifications
- Experience delivering machine learning solutions and integrating into data pipelines.
- Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
- Experience working with or evaluating multi-agent systems or complex GenAI workflows.
What Success Looks Like
- In 90 days: You have successfully onboarded, mastered our data landscape, and begun contributing to active research projects while building relationships with key stakeholders.
- In 6 months: You have delivered your first significant research project with measurable impact and established yourself as a technical leader and effective mentor.
- In 12 months: You have led multiple successful R&D initiatives that have shaped our technical roadmap and been recognized as a subject matter expert who empowers other teams.
About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
- Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best
- We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
- You will also get a new starter budget to kit out your home office
- Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve
- Annual learning budget (prorated based on start date) to drive your performance and career development
About us:
Our mission is to empower every business to eliminate financial crime.
By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.
ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz. Learn more about compliance re-engineered for the age of AI at complyadvantage.com.
Ready to apply?
Apply to ComplyAdvantage
Data Scientist
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Role Summary
As a Data Scientist at ComplyAdvantage, you will develop and refine data-driven solutions to detect and prevent financial crime globally. Your core focus is R&D and Strategic Initiatives, conducting forward-looking research in ML, NLP, and Agentic AI to create measurable business value. In addition to deep-dive R&D, you will provide advisory support to Product and Engineering teams. By investing in AI Enablement workstreams, you will empower these departments with the quantitative insights and frameworks necessary to scale high-impact, AI-driven features.
Key Responsibilities
- Advance R&D in GenAI and Agentic AI: Develop high-impact prototypes for financial crime detection, leveraging multi-agent systems and RAG architectures built on foundational LLM frameworks.
- Contribute to Core Solutions: Collaborate with Engineering and Product to integrate and optimise AI components and frameworks into existing and new product features, ensuring reliability, scalability, and ethical performance in production.
- Evaluate LLM-based Systems: Contribute to the development and implementation of robust evaluation methodologies for LLM and agentic AI based systems, tracking key metrics related to task completion, reasoning accuracy, tool effectiveness, and overall reliability.
- Evaluate Model Context Protocol (MCP) applications: Connect our AI systems with external data sources and tools and provide recommendations for engineering implementation
- Data Understanding: Develop a solid understanding of our existing data sources, identifying challenges and suggesting potential improvements.
- Data Analysis: Use exploratory data analysis and data mining techniques to identify actionable insights for product improvement, including patterns that can inform and refine agent behavior and prompt engineering strategies.
- Research & Innovation: Continuously research and evaluate emerging tools, technologies, and best practices in data science, especially within the rapidly evolving field of Agentic AI, to keep ComplyAdvantage at the forefront.
- Cross-Functional Collaboration: Engage effectively with multi-disciplinary teams to actively share best practices, expertise and inspire innovation to foster an AI-first culture across the organization.
- Visualization & Roadmapping: Provide clear data insights and visualizations that will act as a basis for new ideas to be integrated into our product roadmap.
Required Qualifications
- MSc or PhD in a numerate subject (e.g., Computer Science, Mathematics, Statistics, Physics) or equivalent practical experience in a data-intensive role.
- 2-4 years of professional experience in data science or a related field, with a demonstrated ability to contribute to impactful data-driven solutions.
- Proficiency in Python, including experience with core data science libraries (e.g., Pandas, NumPy, Scikit-learn).
- Hands-on experience with modern machine learning frameworks such as TensorFlow or PyTorch.
- Familiarity with the foundational concepts of agentic AI and large language models (LLMs). This can be professional or through personal research.
- Basic understanding of popular agentic AI frameworks (e.g., LangChain, Pydantic AI).
- Knowledge of general evaluation techniques for AI models and an eagerness to learn and apply methods specific to agentic systems.
- Ability to communicate complex technical concepts effectively to a variety of stakeholders.
- Strong passion for data and solving challenging real-world problems using algorithms.
Preferred Qualifications
- Prior experience contributing to the deployment and integration of machine learning models into production data pipelines.
- Exposure to Big Data platforms such as Spark.
- Experience with Natural Language Processing, Entity Resolution, Graph Theory, or Graph Machine Learning.
- Experience working with or evaluating multi-agent systems or complex AI workflows.
What Success Looks Like
- In 90 days: You have successfully onboarded, gaining a clear understanding of our data landscape and current AI frameworks. You are actively contributing to R&D experiments and have established collaborative working relationships with peers in Engineering and Product.
- In 6 months: You have delivered your first significant R&D prototype or technical evaluation. You have begun contributing to our AI Enablement workstreams, perhaps by authoring a technical blog post or internal guide that translates your research findings into actionable knowledge for the wider team.
- In 12 months: You have completed multiple R&D initiatives that have shaped our technical roadmap. You are recognized for empowering other teams through your advisory support and quantitative expertise, consistently providing the "AI-first" insights that help Engineering and Product teams scale high-impact features.
About Data Science at ComplyAdvantage:
The Data Science tribe discovers and proves out impactful solutions that leverage our Petabyte-scale data infrastructure to neutralise global financial crime. We are responsible for research and development work that drives the "art of the possible" within our product suite. At ComplyAdvantage, we mine the internet for critical data and use it to power a dynamic knowledge graph, which uncovers hidden networks of financial bad actors. From exploring real-time stream processing with Kafka to pioneering the use of the latest LLMs, our modern technology stack allows us to innovate and build prototypes for cutting-edge agentic AI and large-scale algorithmic solutions that empower our clients.
What’s in it for you?
- Equity as we want you to have a part of what we are building
- Private medical insurance designed to keep you ensuring peace of mind while you excel in your career
- Unlimited Time Off Policy- A work-life balance and focus on our well-being are critical to keeping us performing at our best
- We embrace a hybrid approach that requires employees to be in the office for two days a week. We strongly believe that this approach fosters collaboration and enables the building of meaningful relationships
- You will also get a new starter budget to kit out your home office
- Opportunity to work on innovative projects with smart-minded people keen to share their knowledge and continuously improve
- Annual learning budget (prorated based on start date) to drive your performance and career development
About us:
Our mission is to empower every business to eliminate financial crime.
By harnessing AI, a unified platform, and an extensive partner ecosystem, we help customers turn compliance into a catalyst for growth, operational resilience, and enduring regulatory trust.
More than 3,000 enterprises across 75 countries rely on our end-to-end platform and the world’s most comprehensive financial crime risk intelligence. With full-stack agentic automation, we help organizations automate up to 95% of KYC, AML, and sanctions reviews, cut onboarding times by 50%, reduce false positives by 70%, and handle 7x more work with the same staff.
ComplyAdvantage is headquartered in London and has global hubs in New York, Lisbon, Singapore, and Cluj-Napoca. It is backed by Balderton Capital, Index Ventures, Ontario Teachers’ Pension Plan, Goldman Sachs, and Andreessen Horowitz. Learn more about compliance re-engineered for the age of AI at complyadvantage.com.
Ready to apply?
Apply to ComplyAdvantage
We are building a pipeline of talented Machine Learning Engineers for upcoming projects at TensorOps. While we may not have an immediate opening, we are continuously growing and would love to connect with strong candidates for future opportunities.
If you are passionate about ML systems, GenAI, and production-grade deployments, we’d love to hear from you.
About the role
We’re looking for Machine Learning Engineers who enjoy building practical, production-ready AI systems and collaborating on meaningful projects.
In this role, you will:
- Take ownership of key components within ML and GenAI projects, with support from senior team members when needed
- Contribute to architectural and technical decisions in a collaborative environment
- Build scalable ML systems that move from experimentation to real-world application
- Work with international clients to understand requirements and implement thoughtful technical solutions
- Support and mentor junior team members as you grow in your own leadership journey
You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning.
Technical Expertise
We’re looking for engineers with strong hands-on experience across:
- Python: Writing clean, efficient, well-documented, production-quality code
- Machine Learning Frameworks: Designing, training, optimizing, and deploying models independently (e.g., PyTorch, TensorFlow, Scikit-learn)
- GenAI & LLM Systems: Building RAG pipelines, chatbot architectures, and applications using tools like LangChain
- MLOps & Production ML: Model versioning, monitoring, CI/CD for ML workflows
- Cloud Deployments: Deploying and scaling ML systems on AWS, GCP, or Azure
- Performance Optimization & Debugging: Diagnosing complex issues and improving system reliability and efficiency
Requirements
- 2+ years of professional experience in Machine Learning, AI Engineering, or a related role
- Proven experience building and deploying ML models in production environments
- Experience working with stakeholders or clients is a plus
- Bachelor’s degree in Computer Science, Mathematics, Physics, Engineering, or a related field
- Master’s degree in AI, Machine Learning, Computer Science, or a related field is a strong plus
- Equivalent practical experience building and deploying production ML systems will also be considered
What We Offer
- 100% Remote Work: Work from anywhere with flexibility and autonomy
- Dynamic, High-Impact Projects: Work on cutting-edge ML and GenAI solutions across diverse industries
- International Clients: Collaborate with global organizations and solve real-world challenges at scale
- Urban Sports Club Membership: Supporting your physical and mental wellbeing
- Monthly Bolt Credits: For rides
- Company Events & Offsites: Regular team gatherings to connect, collaborate, and celebrate
Ready to apply?
Apply to TensorOps
Machine Learning Engineer
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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
Your achievements matter to us! Ensure your CV and LinkedIn and GitHub profiles are up to date and accurately reflect your experience.
Ready to apply?
Apply to Loka® Inc
Machine Learning Engineer
Share this job
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
Your achievements matter to us! Ensure your CV and LinkedIn and GitHub profiles are up to date and accurately reflect your experience.
Ready to apply?
Apply to Loka, Inc
Senior Machine Learning Engineer
Share this job
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.
Ready to apply?
Apply to Loka® Inc
Senior Machine Learning Engineer
Share this job
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.
Ready to apply?
Apply to Loka, Inc