{"id":12521,"url":"https://alion.io/job/weave-senior-machine-learning-engineer-gen-ai","title":"Senior ML - GenAI Engineer, Voice & Speech","company":{"id":3963,"name":"Weave","domain":"getweave.com","url":"https://alion.io/company/weave","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":82,"open_postings":9,"ghost_share":0,"stale_share":0.667,"repost_share":0.111,"time_to_fill_p50_days":33,"computed_at":"2026-10-23T05:54:15Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":"full_time","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":134000,"max_usd":247000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":338},"experience_years_min":5,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Go","optional":false},{"name":"Java","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"AWS","optional":true},{"name":"Dagster","optional":true},{"name":"DVC","optional":true},{"name":"Embeddings","optional":true},{"name":"Fine-tuning","optional":true},{"name":"GCP","optional":true},{"name":"GitOps","optional":true},{"name":"Google GKE","optional":true},{"name":"HIPAA","optional":true},{"name":"Kubeflow","optional":true},{"name":"Kubernetes","optional":true},{"name":"MLFlow","optional":true},{"name":"Model Context Protocol","optional":true},{"name":"Multimodal AI","optional":true},{"name":"PostgreSQL","optional":true},{"name":"Prompt Engineering","optional":true},{"name":"RAG","optional":true},{"name":"Speech Recognition","optional":true},{"name":"Triton","optional":true}],"status":"live","first_seen_at":"2026-04-02T21:52:01Z","employer_posted_date":"2026-04-02","last_verified_at":"2026-10-23T15:47:09Z","board_verified":true,"closed_at":null,"days_open":203,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":203},"description":"Weave is looking for engineers hungry for fun challenges who can join our self-empowered teams and contribute in both technical and non-technical ways.\nYou will be joining a team of talented developers that share a common interest in distributed backend systems, data, scalability, and continued development. You will get a chance to apply these and other skills to new and ongoing projects to make machine learning more approachable, data more available, and easier to discover and use by helping design how teams build out AI-powered features at Weave.\nOur teams are cross-functional agile teams composed of a product owner, backend and frontend devs and DevOps. Teams are highly autonomous with the ownership and ability to act in Weave’s best interest.\nAbove all, your work will impact the way our customers experience Weave while working closely with a highly skilled team to accomplish varying goals and cultivate our phenomenal culture.\nPURPOSE\nThe Machine Learning Team's mission is to enable product innovation by making it painless for developers to build AI-powered applications that require access to large sets of data. Machine learning is challenging, but we are striving to democratize access to the tools and technology that power it so teams can build cutting-edge features safely and responsibly without a PhD in Data Science. As a Machine Learning Engineer on the team, you’ll be building models for new products with emerging technologies, at scale. We handle data for hundreds of millions of people daily.\nThis position will be available fully remote in the US with an opportunity to work in an office if located near the Lehi, UT Headquarters.\n\nReports to: Engineering Director\n\nWhat You Will Own\nDesign and develop machine learning infrastructure, tooling, and models to help teams deliver world-class experiences.\n\nHelp product and development teams understand the data lifecycle and the inherent experimental nature of machine learning.\n\nBuild internal products and platforms to enable teams to incorporate AI into their features and customer-facing products.\n\nConsult with teams to help them understand common patterns, anti-patterns, and trade-offs of machine learning. Guide them through creating excellent customer experiences end to end.\n\nBuild scalable, resilient services to support data integration, event processing, and platform extensions.\n\nContribute to the continued evolution of product functionality that services large amounts of data and traffic.\n\nWrite code that is high-quality, performant, sustainable, and testable while holding yourself accountable for the quality of the code you produce.\n\nCoach and collaborate inside and outside the team. You enjoy working closely with others - helping them grow by sharing expertise and encouraging best practices.\n\nWork in a cloud environment, considering the implementation of functionality through several distributed components and services.\n\nWork with our stakeholders to translate product goals into actionable engineering plans.\n\nWhat You Will Need to Accomplish the Job\nHigh integrity, team-focused approach, and collaboration skills to build tight-knit relationships across Weave with various roles and stakeholders.\n\nResponsive person with a strong bias for action.\n\n5+ years of experience in any structured back-end language, i.e. Go, Java or Python (Go and Python experience is a plus).\n\nExperience moving and storing TBs of data or 100 M to 10 B records.\n\nExperience building and deploying ML-driven B2B multi-tenant applications in production environments.\n\nExperience with common ML technologies such as Python, Jupyter, Workflow Engines (Dagster, MLflow, Kubeflow, etc.), DVC, Triton Server, LLMs, Postgres, and others.\n\nExperience with modern ML tools and techniques such as LLMs, RAG, Prompt Engineering, fine-tuning, multimodal models, and others.\n\nExperience with data labelling or annotation for audio or text use cases.\n\nUnderstanding of distributed systems and building scalable, redundant, and observable services.\n\nExpertise in designing and architecting systems for distributed data sets and services.\n\nExperience building solutions to run on one or more of the public clouds (e.g., AWS, GCP, etc.).\n\nExperience providing stable, well-designed libraries and SDKs for internal use.\n\nSelf-driven and a thirst for learning in a quickly changing industry.\n\nDemonstrated track record of delivering complex projects on time and experience working in enterprise-grade production environments.\n\nStrategic thinker with a strong technical aptitude and a passion for execution.\n\nWhat Will Make Us Love You\nA background in data analysis, visualization, and presentation.\n\n3+ years of experience in data science, machine learning, or predictive analytics in addition to engineering experience.\n\nExperience with natural language models, embeddings, and inference in production, at scale.\n\nExperience with real-time audio models and voice use cases such as transcription, ASR pipelines with interruption detection, audio alignment, and speech synthesis.\n\nExperience with emerging technologies such as Model Context Protocol (MCP).\n\nProficient understanding of containers, orchestrators, and usage patterns at scale, including networking, storage, service meshes, and multi-cluster communication. Experience with Kubernetes or GKE and the Operator Pattern (GCP), specifically, is a plus.\n\nExperience with highly sensitive data such as PHI (HIPAA) and PII data.\n\nExperience with automation and container-based workflow engines.\n\nExperience with GitOps, IaC, and configuration-driven systems.\n\nA preference for open source solutions.\n\nA track record of clean abstractions and simple-to-use APIs.\n\nDeep understanding of distributed data technologies such as streaming, data mesh, data lakes, warehouses, or distributed machine learning.\n\nA desire to advance the state of the art with new and innovative technologies.\n\nEnjoys working in a greenfield environment using rapid prototyping.\n\nEnjoys working with open-ended, evolving problems and domains.\n\nEmployment with Weave is contingent upon the successful completion of a background check, conducted in accordance with applicable laws.\nAt Weave, we use Artificial Intelligence (AI) tools to help us work more efficiently and create a smoother candidate experience. AI may assist with things like writing job descriptions, scheduling interviews, or reviewing applications against job-related criteria. For additional information, please review the External AI Policy Statement available on our Careers page.\nWeave is an equal opportunity employer that is committed to fostering an inclusive workplace where all individuals are valued and supported. We welcome anyone who is hungry to learn, problem-solve and progress regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity, veteran status, or other applicable legally protected characteristics. If you have a disability or special need that requires accommodation, please let us know.\nBeware of recruitment fraud. All official correspondence will occur through Weave branded email. 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