Role Description - Design, Entwicklung und Optimierung von Machine-Learning- und Deep-Learning-Modellen - Konzeption, Implementierung und Optimierung von NLP-Lösungen, LLMs sowie RAG-Architekturen - Aufbau von Retrieval- und Knowledge-Layern für semantische Suche mit Embeddings sowie Vektor- oder Graph-Datenbanken - Aufbau, Deployment und Betrieb von ML- und GenAI-Services - Aufbau und Betrieb skalierbarer Datenpipelines Qualifications - Mindestens 7 Jahre Berufserfahrung als AI / ML / Data Engineer - Abgeschlossenes Studium der Informatik, Mathematik, Physik, Data Science oder vergleichbare Qualifikation - Mehrjährige Erfahrung mit Programmiersprachen wie Python - Fundierte Fachkenntnisse in der Entwicklung und Optimierung von Machine-Learning- und Deep-Learning-Modellen mit TensorFlow oder PyTorch - Umfassende Erfahrung in NLP sowie mit LLM- und RAG-Architekturen - Berufserfahrung im Aufbau von Retrieval- und Knowledge-Layern für semantische Suche mit Embeddings sowie Vektor- oder Graph-Datenbanken - Sehr gute Kenntnisse im Aufbau und Betrieb skalierbarer Datenpipelines mit Apache Spark oder SQL und ETL-Tools Benefits - Fixgehalt ab 80.000 € mit Gewinnbeteiligung bis zu 70.000 € - Flexible Arbeitszeiten und Remote-Arbeit - 30 Tage Urlaub - IT-Equipment wie Apple MacBook - Regelmäßige Teamevents - Corporate Benefits wie betriebliche Altersvorsorge, betriebliche Krankenversicherung, Shopping- und Mitarbeiterrabatte

Role Description As a Senior Software Engineer on the Data Platform team, you will be responsible for executing mission-critical systems and data services that analyze blockchain transaction activity at petabyte scale, and ultimately work to build a safer financial system for billions of people. - Build highly reliable data services to integrate with dozens of blockchains. - Develop complex ETL pipelines that transform and process petabytes of structured and unstructured data in real-time. - Design and architect intricate data models for optimal storage and retrieval to support sub-second latency for querying blockchain data. - Oversee the deployment and monitoring of large database clusters with an unwavering focus on performance and high availability. - Collaborate across departments, partnering with data scientists, backend engineers, and product managers to design and implement novel data models that enhance TRM’s products. Qualifications - A Bachelor's degree (or equivalent) in Computer Science or a related field. - A proven track record, with 5+ years of hands-on experience in architecting distributed system architecture, guiding projects from initial ideation through to successful production deployment. - Exceptional programming skills in Python, as well as adeptness in SQL or SparkSQL. - Versatility that spans the entire spectrum of data engineering in one or more of the following areas: - In-depth experience with data stores such as Iceberg, Trino, BigQuery, and StarRocks, and Citus. - Proficiency in data pipeline and workflow orchestration tools like Airflow, DBT, etc. - Expertise in data processing technologies and streaming workflows including Spark, Kafka, and Flink. - Competence in deploying and monitoring infrastructure within public cloud platforms, utilizing tools such as Docker, Terraform, Kubernetes, and Datadog. - Proven ability in loading, querying, and transforming extensive datasets. Requirements - Build scalable engines to optimize routine scaling and maintenance tasks. - Enable tasks to be faster next time and reduce dependency on a single person. - Identify ways to compress timelines using the 80/20 principle. - Identify first version, a.k.a., "skateboards" for projects. Benefits - Remote-first and async friendly environment. - High level of personal ownership and accountability. - Close collaboration across teams and functions. - Creative problem solving and out-of-the-box thinking. - A pace that rewards urgency, adaptability, and outcomes. Company Description TRM Labs provides AI-powered intelligence solutions that help public and private sector agencies investigate and disrupt crime. TRM's platforms enable investigators to trace illicit activity, build cases, and construct operating pictures of threat networks. TRM is a Series C company with $220M in total funding, backed by Blockchain Capital, Goldman Sachs, Bessemer, Y Combinator, Thoma Bravo, and others. Headquartered in San Francisco, TRM operates as a distributed-first company with hubs in Los Angeles, San Francisco, New York, Washington D.C., London, and Singapore.

Role Description We are on a mission to build machines that understand the world and make them safely accessible to all. Data quality is foundational to this process. Machines (or Large Language Models to be exact) learn in similar ways to humans: by way of feedback. By labeling, ranking, auditing, prompting, red teaming, and correcting output, you will improve Large Language Model’s performance for iterations to come, thus having a lasting impact on Cohere’s tech. Cohere is looking for Data Annotation Specialists with backgrounds and skills in Trust & Safety, Content Moderation, AI model evaluation, or related fields. This role is best suited for candidates who bring: - Strong contextual judgment - Cultural and bias sensitivity - Experience applying nuanced guidelines to complex or ambiguous content Successful candidates will be highly detail-oriented, comfortable evaluating safety risks across different user intents and scenarios, and able to make consistent, well-reasoned decisions with a high degree of independence after onboarding. IMPORTANT CONTEXT ON THIS ROLE: In this position, you will be asked to engage with human-generated and model-generated tasks which will sometimes mean intentional exposure to explicit content. Your annotations on these explicit tasks will be used to prevent the Large Language Model from generating unintentional, adversarial, toxic, or unsafe outputs. The types of explicit content you may be exposed to may include but are not limited to those of a sexual, violent, or psychologically disturbing nature. Please Note: This is a part-time, remote, independent contractor position available within Canada or the United States. We seek candidates who are able to commit to 16 hours per week minimum at a 45 CAD/hour or 45 USD/hour contract rate, depending on your location, consisting of 30/hour base pay plus 15/hour hazard pay. This role is BYOD 💻 - Bring Your Own Device (laptop). 12 months contract with potential for extension. As a Data Annotation Specialist on safety task, you will: - Evaluate and improve model safety: - Label, rank, audit, and refine human- and model-generated text to improve safety, quality, and policy alignment, including content that may be sexual, violent, or psychologically disturbing. - Apply nuanced safety judgment: - Assess model outputs against detailed safety guidelines, rubrics, and style standards, making consistent decisions across ambiguous, sensitive, and context-dependent cases. - Create prompts and safety test cases: - Write realistic prompts, user scenarios, and adversarial examples that help evaluate model behavior across safety categories and uncover unsafe, evasive, over-refusing, or policy-inconsistent responses. - Support quality and calibration: - Identify annotation inconsistencies or unclear guidelines, and provide actionable feedback on recurring edge cases, model failures, and opportunities to improve data quality. - Work with precision and independence: - Complete annotation tasks with strong attention to detail, while being comfortable working independently in a globally distributed, asynchronous team environment. Qualifications - 1+ years of experience in Content Moderation, Trust and Safety, AI data annotation, LLM evaluation, or a related analytical role, with exposure to quality assurance, red teaming, and/or prompt engineering preferred. - Experience applying detailed guidelines to complex and sensitive content, with strong contextual and sociocultural judgment and the ability to recognize and manage personal bias. - Emotional resilience: Comfort working with content that contains unsafe, explicit, and/or toxic content, including content of a sexual, violent, or psychologically disturbing nature. - Excellent command of written English and the ability to clearly justify content evaluations, including why an output is safe, unsafe, high-quality or low-quality. Bonus points if you are fluent in another language! - Strong attention to detail and commitment to accuracy, with the ability to maintain consistency across high-volume and monotonous tasks. - Strong execution in a remote environment, including good time management, comfort using new tools, and the ability to work independently in a global, asynchronous team. Candidate Journey - Initial Screening - Once you have submitted your application our Talent Team will review your resume and writing samples. - Virtual Annotation Test - This assignment will test your written skill through various language-based tasks, such as a writing sample, interacting with a chat bot, and more. - Video Screen - If selected to move forward, you will have a short video call with a member of our Operations Team! Benefits - An open and inclusive culture and work environment - Work closely with a team on the cutting edge of AI research - Weekly lunch stipend, in-office lunches & snacks - Full health and dental benefits, including a separate budget to take care of your mental health - 100% Parental Leave top-up for up to 6 months - Personal enrichment benefits towards arts and culture, fitness and well-being, quality time, and workspace improvement - Remote-flexible, offices in Toronto, New York, San Francisco, London and Paris, as well as a co-working stipend - 6 weeks of vacation (30 working days!)

Role Description As a Senior or Lead Backend Engineer on our Applied AI team, you will be at the forefront of integrating robust data engineering with next-generation AI capabilities. You will design, build, and maintain scalable backend systems and data pipelines that power critical functions across our platform — from fraud investigation and decision automation to process optimization. In this role, you will champion high data quality, system reliability, and stringent governance across all AI-driven initiatives, making a lasting impact on FICO's platform. This is an opportunity to collaborate with a high-caliber team and drive meaningful innovation through your deep expertise in backend engineering and applied AI. What You'll Contribute - Design and deploy scalable backend systems and data pipelines that seamlessly integrate applied AI capabilities into FICO's analytics and decision management platform. - Build high-quality solutions for data ingestion, transformation, and storage, ensuring reliable, high-throughput data flow for real-time analytics. - Design and implement LLM-powered solutions for decision automation, fraud investigation, and process automation within FICO's platform. - Develop sophisticated prompting strategies and Retrieval-Augmented Generation (RAG) architectures tailored to high-stakes, mission-critical applications. - Partner with data scientists, ML engineers, and product teams to develop microservices and APIs that enable intelligent, data-driven decision-making. - Optimize distributed architectures and implement real-time processing frameworks to support high-volume, low-latency workloads. - Implement advanced monitoring, testing, and performance optimization techniques to ensure system reliability, security, and scalability. - Define and evolve architectural patterns that support FICO's analytics and decisioning solutions at scale. - Lead and mentor engineering team members, promoting best practices in software development, data engineering, AI integration, and systems design. Qualifications - 7+ years of experience in backend or data engineering, with a demonstrated track record of delivering complex, large-scale production systems. - Strong coding skills in Python, Go, Java, or equivalent languages, with a commitment to clean, maintainable, and well-tested code. - Hands-on experience with big data frameworks (e.g., Apache Spark, Kafka, Hadoop) and a strong understanding of both relational and NoSQL databases. - Experience with cloud platforms (AWS, GCP, or Azure) and container orchestration tools such as Docker and Kubernetes. - Proven ability to design, build, and maintain scalable, production-grade backend systems with a focus on reliability and performance. - Solid experience with testing frameworks (including A/B testing), performance optimization, and production monitoring/observability practices. - Demonstrated experience integrating AI/ML solutions into production systems, including working with Large Language Models (LLMs) and related techniques. - Experience with Retrieval-Augmented Generation (RAG) architectures and familiarity with vector databases (e.g., Pinecone, Weaviate, pgvector) is strongly preferred. - Strong problem-solving and communication skills, with the ability to mentor engineers, influence technical direction, and collaborate effectively across disciplines. - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. An advanced degree is a plus but not required. Benefits - An inclusive culture strongly reflecting our core values: Act Like an Owner, Delight Our Customers and Earn the Respect of Others. - The opportunity to make an impact and develop professionally by leveraging your unique strengths and participating in valuable learning experiences. - Highly competitive compensation, benefits and rewards programs that encourage you to bring your best every day and be recognized for doing so. - An engaging, people-first work environment offering work/life balance, employee resource groups, and social events to promote interaction and camaraderie. - The targeted base pay range for this role is: $140,000 to $220,000 with this range reflecting differences in candidate knowledge, skills and experience.