4 Meltano Jobs

As a Machine Learning Operation Engineer at Onclusive, you will play a crucial role in deploying, scaling, and optimizing backend algorithms, data ingestion pipelines, machine learning services, and data platforms. Your expertise will be utilized to support the analysis of vast amounts of text and analytics data, helping to solve challenging marketing problems using Onclusive's billions of online content data points. Your responsibilities will include designing and building scalable machine learning services and data platforms, utilizing benchmarks and metrics to measure and improve services, managing systems processing tens of millions of jobs per day, researching and implementing cutting-edge algorithms, and collaborating with data scientists and machine learning engineers on ML, AI, and NLP techniques for article analysis and attribution. Additionally, you will deploy, manage, and optimize inference services on autoscaling fleets with GPUs and specialized inference hardware. The ideal candidate for this role will have a degree (BS, MS, or Ph.D.) in Computer Science or a related field, accompanied by hands-on experience. Proficiency in Python with a strong understanding of Object-Oriented Programming (OOP) principles is required. Knowledge of containerization (preferably Docker), experience with Kubernetes and Infrastructure as Code (IAC) for AWS (preferably Terraform), familiarity with Version Control Systems (VCS) like Git and GitHub, CI/CD (preferably GitHub Actions), and good understanding of ML principles are essential. Data Engineering experience and exposure to deep learning tech-stacks like Torch/Tensorflow and Transformers are highly desired. Onclusive offers a global, fast-growing environment with opportunities for skill development and career growth. In return for your contributions, you can expect a competitive salary and benefits, hybrid working arrangements, a supportive team passionate about their work, and a focus on wellbeing and work-life balance through initiatives such as flexible working and mental health support.,

About the Role: As a Machine Learning Operation Engineer, you will work on deploying, scaling, and optimizing backend algorithms, robust and scalable data ingestion pipelines, machine learning services, and data platforms to support analysis on vast amounts of text and analytics data. You will apply your technical knowledge and Big Data analytics on Onclusives billions of online content data points to solve challenging marketing problems. ML Ops Engineers are integral to the success of Onclusive. Your responsibilities: Design and build scalable machine learning services and data platforms. Utilize benchmarks, metrics, and monitoring to measure and improve services. Manage system currently processing data on the order of tens of millions of jobs per day. Research, design, implement and validate cutting-edge algorithms to analyze diverse sources of data to achieve targeted outcomes. Work with data scientists and machine learning engineers to implement ML, AI, and NLP techniques for article analysis and attribution. Deploy, manage, and optimize inference services on autoscaling fleets with GPUs and specialized inference hardware. Who you are: A degree (BS, MS, or Ph.D.) in Computer Science or a related field, accompanied by hands-on experience. Minimum 2 years experience of Kubernetes and/or Terraform Proficiency in Python, showcasing your understanding of Object-Oriented Programming (OOP) principles. Solid knowledge of containerisation (Docker preferable) Experience in Infrastructure as Code (IAC) for AWS, with a preference for Terraform. Knowledge of Version Control Systems (VCS), particularly Git and GitHub, alongside familiarity with CI/CD, preferably GitHub Actions. Understanding of release management, embracing rigorous testing, validation, and quality assurance protocols. Good understanding of ML principles Data Engineering experience (airflow, dbt, meltano) is highly desired. Exposure to deep learning tech-stacks like Torch / Tensorflow, and Transformers. What we can offer: We are a global fast growing company which offers a variety of opportunities for you to develop your skill set and career. In exchange for your contribution, we can offer you: Competitive salary and benefits Hybrid working in a team that is passionate about the work we deliver and supporting the development of those that we work with A company focus on wellbeing and work life balance including initiatives such as flexible working and mental health support We want the best talent available, regardless of race, religion, gender, gender reassignment, sexual orientation, marital status, pregnancy, disability or age. Show more Show less

About the Role: As a Machine Learning Operation Engineer at Onclusive, your primary responsibility will be to deploy, scale, and optimize backend algorithms, robust data ingestion pipelines, machine learning services, and data platforms to handle vast amounts of text and analytics data. You will leverage your technical expertise and Big Data analytics skills to address complex marketing challenges using Onclusive's extensive online content data. The role of an ML Ops Engineer is crucial to the success of Onclusive. Your responsibilities include designing and constructing scalable machine learning services and data platforms, utilizing benchmarks and metrics to enhance services, overseeing a system processing tens of millions of jobs daily, researching and implementing cutting-edge algorithms for data analysis, collaborating with data scientists and ML engineers on implementing ML, AI, and NLP techniques, and managing inference services on autoscaling fleets with GPUs and specialized hardware. Who you are: You hold a degree (BS, MS, or Ph.D.) in Computer Science or a related field, supported by practical experience. You should have a minimum of 2 years of experience with Kubernetes and/or Terraform, proficiency in Python with a solid grasp of Object-Oriented Programming principles, knowledge of containerization (preferably Docker), experience in Infrastructure as Code (IAC) for AWS (preferably Terraform), familiarity with Version Control Systems (particularly Git and GitHub) and CI/CD (preferably GitHub Actions), understanding of release management with a focus on testing and quality assurance, good grasp of ML principles, and desirable experience in Data Engineering tools like airflow, dbt, and meltano. Exposure to deep learning tech-stacks such as Torch, Tensorflow, and Transformers is a plus. What we can offer: Joining a rapidly growing global company, you will have the opportunity to enhance your skills and advance your career. In return for your contributions, we provide a competitive salary and benefits, a hybrid working environment within a team passionate about their work and supporting each other's development, and a company culture that prioritizes wellbeing and work-life balance through initiatives like flexible working arrangements and mental health support.,

Job Description : We are seeking a versatile and passionate Full Stack Engineer to contribute across our entire application stack. You will be responsible for both Back-end user interfaces and Front-end services, ensuring seamless integration, optimal performance, and an exceptional user experience. This role requires a strong understanding of modern web technologies and the ability to adapt to diverse technical challenges. Required Skills : 6+ years of full-stack web development experience, with deep expertise in Python and hands-on experience with frameworks like Django REST Framework- DRF, and FastAPI for scalable back-end services. Backend Expertise: Solid experience with Python, particularly FastAPI, and Django (including Django REST Framework - DRF). Practical experience with MySQL and other relational databases. Experience with Kafka for building event-driven systems Frontend Expertise: Proficiency in React.js for building interactive and responsive user interfaces. Strong command of TypeScript and JavaScript, HTML5, and CSS3. Experience deploying and managing applications on cloud services. Demonstrated ability to design and implement RESTful APIs and work with GraphQL. Proficiency in version control systems (e.g., Git). Proven track record in coding, testing, and process adherence. Exceptional problem-solving capabilities and analytical skills, with a keen eye for both front-end usability and back-end scalability. Excellent verbal and written communication skills in English for effective cross-functional collaboration. Preferred Qualifications : Familiarity with WebSockets for real-time features. Understanding of containerization technologies like Docker and orchestration with Kubernetes. Exposure to Generative AI libraries and other AI/ML Python libraries for integrating intelligent features across the stack. Experience with NoSQL databases like ArangoDB or vector databases. Knowledge of Redis for caching. Familiarity with Snowflake or Spark for data processing and analysis. Experience with Meltano for data integration pipelines. Exposure to HAProxy for load balancing. Proficiency in other programming languages in our stack (e.g., PHP). Cultural Fit : Innovation catalyst: Thrives on incorporating cutting-edge technologies like GenAI into practical, scalable solutions Enterprise empathy: Understands the complexity of enterprise environments and designs solutions that work in real-world business contexts Startup agility: Comfortable with rapid iteration, changing requirements, and building for both current needs and future scale Collaborative builder: Values cross-functional teamwork and contributes to a culture of technical excellence Continuous learner: Stays at the forefront of cloud technologies, AI advancements, and distributed systems best practices Personal Attributes : Proactive and Detail-Oriented Self-motivated individual contributor with a strong focus on quality, precision, and thoughtful software development. Strong Interpersonal Skills Adept at engaging with stakeholders across disciplines, ensuring alignment, clarity, and shared success.