Role Description We're in search of a talented Staff MLOps Engineer to join our team. This role is pivotal in spearheading the development and maintenance of our machine-learning infrastructure and processes. If you're passionate about optimizing machine learning systems for scalability, reliability, and efficiency, and have a strong background in data engineering and DevOps, we want to hear from you. - Lead the design, implementation, and maintenance of a robust infrastructure for deploying, monitoring, and managing machine learning models in production environments. - Develop and automate end-to-end pipelines for data ingestion, preprocessing, feature engineering, model training, evaluation, and deployment. - Collaborate closely with data scientists to understand model requirements and optimize model performance for production use. - Establish and maintain CI/CD pipelines to streamline the deployment process and ensure reproducibility. - Design and implement monitoring and alerting systems to track model performance and health, and proactively identify and address issues. - Optimize system architecture and resource utilization to ensure scalability, reliability, and cost-effectiveness. - Stay abreast of industry best practices and emerging technologies in MLOps, data engineering, and DevOps, and integrate them into our processes and infrastructure. - Provide technical leadership and mentorship to junior team members, and drive innovation and continuous improvement across the organization. Qualifications - Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. - 6+ years of experience in MLOps, data engineering, and/or DevOps roles. - Proficiency in programming languages such as Python, Java, Scala, or Ruby, we work with Python primarily. - Experience working with large language models (LLMs) and LangChain, or similar tools, a plus. - Extensive experience with cloud platforms such as AWS, Azure, or GCP, and proficiency in using cloud services for storage, compute, and orchestration. - Strong understanding of containerization and orchestration technologies such as Docker, and Kubernetes. - Experience with infrastructure as code (IaC) tools such as Terraform, or Terragrunt. - Solid background in designing and optimizing data pipelines using technologies like Apache Airflow, or similar. - Exceptional analytical and problem-solving skills, with a proactive approach to identifying and resolving issues. - Excellent communication and collaboration skills, with the ability to lead cross-functional teams and mentor junior members effectively. Requirements - Building a product that really improves users’ lives (70k users, 4.6 rates at App Store). - Being a part of a global team that builds a diverse culture in our company. - Working with more than 200 engineers highly qualified and engaged in improving the life of our Pros. - Having a real impact on technical decisions without breaking through the corporate glass ceiling. - Being in direct contact with the community of users, who are eager to share their feedback. - Rapidly growing teams that create a defined career path. Benefits - Remote environment totally built to make you feel that we are all together in one space without leaving your home office! - Self Managed PTO - Beach? Mountains? Camping? Discovering new experiences? You are free to take time out as you need! - Flexible work hours - We believe that you can reach your professional and personal goals working with us and encourage you to have a work-life balance! - A culture built on innovation that values big ideas - We are always open to new ideas that will improve the life of our Pros! - Work in your own time zone - Because we don’t think that you should miss those memorable moments with your friends and family! - Newest MacBook (or PC if you prefer!) + Setup Fee ($500) - What is an engineer without the right tools right? Here in HCP, you can choose your computer and set up your home office!

Role Description We are looking for a senior-level ML expert with deep experience in Speech AI, ideally focused on TTS / Voice Generation, to help build and scale production-grade speech systems. This is a highly hands-on role for someone who combines strong research capabilities with real-world production experience and can operate effectively in a fast-moving startup environment. Qualifications - 5+ years of experience in Speech AI, preferably TTS / Voice Generation - TTS has been a primary focus in recent years - Hands-on experience training and fine-tuning TTS models - Proven experience deploying ML models into real production environments - Strong understanding of inference, latency, scaling, monitoring, and reliability - Strong ML background overall (ML Scientist / ML Engineer trajectory) - Strong coding and engineering skills Requirements - Develop and improve TTS / Voice Generation models - Train, fine-tune, and evaluate speech models - Bring research ideas into production systems - Work across research, engineering, and product - Help define technical direction and ML best practices - Drive execution in a fast-changing environment - Collaborate closely with engineering, product, and business stakeholders Benefits - Experienced team, Acclaim is formed by a team of enthusiastic professionals who have created award-winning devices, voice assistants, and other AI-driven products for BigTech corporations - Cutting-edge technologies, we build technologies using our areas of expertise, including Computer Vision, Speech Technologies, Natural Language Understanding, Generative AI, etc. LLM and Diffusion models - Rapid career progression, facilitated by our team of seasoned senior professionals who hail from prestigious, industry-leading companies - Remote work opportunities from Europe / US - The company has prominent clients with an opportunity for you to work on different projects and/or to be involved in developing our proprietary products - A company with entrepreneurial spirit. We offer a secure workspace, thanks to the big clients we've raised, along with a true start-up culture.

• Own and scale ML-driven Marketing/Growth/Product capabilities • Lead development and deployment of core models, including Propensity, Churn prevention, Customer Lifetime Value models • Improve onboarding, targeting, personalization, and segmentation at scale • Continuously evaluate and improve marketing spend efficiency through ML-driven insights and models • Partner closely with Marketing, Product, and Finance to align ML investments with business priorities • Set standards for model development, experimentation, and validation • Design and optimize reward and incentive strategies to maximize user acquisition, activation, and retention

• Design and run experiments to improve agent quality: better tool use, better reasoning, better outputs, using frameworks like DSPy and VLLM • Build and maintain evaluation infrastructure to measure what's working and catch regressions before customers do • Optimize LLM inference: latency, cost, model routing, and quality tradeoffs • Partner with product teams on model selection and performance benchmarking • Work closely with product engineers and PMs to translate customer quality problems into ML hypotheses and solutions • Own models end-to-end: from research and experimentation to production deployment