Svitla Systems is a global digital solutions company headquartered in California, with business and development offices throughout the US, Latin America, Europe, and Asia. Svitla is an outspoken advocate of workplace flexibility, best known for its well-established remote culture, individual approach to our teammate’s professional and personal growth, and trustworthy environment.
Since 2003, Svitla has served a wide range of clients, from innovative start-ups in California to mega-large corporations such as Ingenico, Amplience, InvoiceASAP and Global Citizen. At Svitla, developers work with clients’ teams directly, building lasting and successful partnerships, as a result of seamless integration with on-site processes.
Svitla Systems’ global mission is to build a business that contributes to the well-being of our partners, personnel and their families, improves our communities, and makes a lasting difference in the world. Join us! The Opportunity Svitla Systems Inc. is looking for a Senior MLOps Engineer for a full-time position (40 hours per week) in Ukraine and the EU.
Our client is an early-stage AI startup founded in 2024 and headquartered in Columbia, South Carolina. The company was founded by five experienced entrepreneurs with diverse backgrounds, including AI and tech startups. In April 2025, they closed a $2 million seed funding round from investors based in South Carolina and Oklahoma.
They develop a human-centered, emotionally aware AI chat agent with customizable personalities that can serve as a witty companion, insightful consultant, or strategic advisor. Their technology supports multiple GPU platforms (ROCm, Metal, CUDA) and emphasizes creating natural, human-like interactions.
Currently in alpha/beta, with free and Pro access tiers (Pro offers higher token limits), the company is rapidly growing and expanding its engineering team globally.
You will join their innovative Research & Development team to build and deploy robust, scalable machine learning systems. In this role, you’ll apply your software engineering skills to operationalize ML models and contribute to the infrastructure, tools, and processes powering AI-driven products. Collaborating closely with machine learning engineers, data scientists, and software engineers, you will bridge the gap between model development and real-world applications.
Key research papers informing their work include: * MegaByte: arxiv.org/pdf/2305.07185 * Mamba: arxiv.org/pdf/2312.00752 * MambaByte: arxiv.org/pdf/2401.13660
Familiarity with these papers provides valuable context for their innovative ML solutions.
Requirements * Bachelor’s, Master’s, or PhD in Computer Science, Software Engineering, a closely related technical field, or equivalent experience (10+ years). * Extensive, proven experience (typically 5+ years, or 3+ with a PhD) in machine learning engineering, software engineering focusing on ML systems, or a similar role. * Expert-level proficiency in Python and proficiency in at least one language relevant to high-performance systems (e.g., C++, Java, Go, Rust). * Hands-on expertise in building and deploying complex machine learning models and systems into production environments. * In-depth understanding of MLOps principles, tools, and platforms (e.g., MLflow, Kubeflow, TFX, Seldon Core, Docker, Kubernetes, CI/CD for ML, model registries, feature stores). * Experience with major cloud platforms (e.g., AWS, Azure, GCP), including their advanced ML services, compute options, and infrastructure components. * Expert understanding of machine learning lifecycle, distributed systems, microservices, and data engineering principles. * Demonstrated ability to develop complex technical projects, mentor engineers, and execute technical strategy. * Exceptional problem-solving, debugging, and system design skills, with the ability to execute on solutions for ambiguous and challenging requirements. * Outstanding communication and interpersonal skills, with the ability to articulate complex technical designs and strategies to technical and executive audiences.
Nice to have * Significant contributions to open-source MLOps, machine learning, or distributed systems projects. * Expertise in designing and implementing solutions for real-time, low-latency ML inference at scale. * Knowledge of specific hardware acceleration for ML (e.g., GPUs, TPUs, FPGAs) and experience with CUDA programming or similar. * Experience building and managing large-scale data processing pipelines using technologies like Spark, Flink, Kafka, or Beam. * Expertise in network programming, distributed consensus, or high-availability system design. * Advanced knowledge of C++ for building and optimizing high-performance ML inference pipelines or system components. * Experience with security best practices for ML systems and data. * A track record of publications in top-tier engineering or ML systems conferences/journals.
Responsibilities * Design, develop, and deploy mission-critical machine learning systems, platforms, and infrastructure, ensuring best-in-class reliability, scalability, and performance. * Execute the organization’s technical vision and strategy for MLOps practices, tools, and frameworks. * Own and oversee the end-to-end lifecycle of complex ML systems, from requirements gathering and system design to implementation, testing, deployment, and long-term operational excellence. * Provide technical leadership, mentorship, and guidance to machine learning engineers, fostering a culture of innovation, collaboration, and engineering excellence. * Champion and enforce software engineering and MLOps best practices, including advanced CI/CD for ML, automated testing, infrastructure-as-code, comprehensive monitoring, and proactive incident response. * Collaborate with data scientists to understand model intricacies and translate research prototypes into production-grade systems. * Spearhead the optimization of machine learning models and inference pipelines for ultra-low latency, high throughput, and optimal resource utilization on various hardware platforms. * Help lead the evaluation, selection, and integration of new technologies, tools, and methodologies to enhance our ML engineering capabilities. * Drive initiatives to improve our ML infrastructure’s scalability, reliability, and cost-effectiveness. * Troubleshoot and resolve challenging issues in production ML systems, often requiring deep dives into complex, distributed environments.
We offer * US and EU projects based on advanced technologies. * Competitive compensation based on skills and experience. * Annual performance appraisals. * Flexibility in workspace, either remote or in one of our development offices. * Comprehensive medical insurance including dental and massages. * Sport reimbursement program for onsite and online activities. * Support of a healthy lifestyle, compensation for running events. * Bonuses for recommendations of new employees. * Bonuses for article writing, public talks, other activities. * Personal loan budget available for long-term personnel. * 20 vacation days, 10 national holidays and sick leaves. * Maternity leave policy and family days off. * Full compensation for conferences, courses, English classes. * Free webinars, meetups and conferences organized by Svitla. * Gifts for New Year, anniversaries, children, and more. * Fun corporate celebrations and activities, regular lectures on various topics. * Awesome team, friendly and supportive community!
