[Remote] Senior Machine Learning Engineer, Content Engineering

Note: The job is a remote job and is open to candidates in USA. Paramount is on a mission to unleash the power of content and is seeking a Senior Machine Learning Engineer to lead the development of multimodal embedding and retrieval systems for content discovery. The role involves owning the full lifecycle of multi-modal embedding systems and collaborating with various teams to enhance user engagement with video content.ResponsibilitiesDesign and build embedding pipelines for video content metadata and clip-level representationDesign collection and vector schemas to shape data structure, indexing behavior, and retrieval performance under scale and modality complexityLead the transition from traditional feature engineering to a vector-centric "context-first" architecture, through compositional queries and by designing high-dimensional hyper-vector representations that unify visual, textual, and behavioral signalsDesign offline/online evaluation frameworks (e.g., nDCG, MRR, Recall@K) specifically for multimodal alignment, ensuring content embeddings match search intentBuild hybrid retrieval systems that combine vector similarity search with lexical search and reranking layers to deliver fast, accurate, and scalable performance at production scaleEngineer the retrieval layer to capture nuanced user-content relationships that model training alone cannot surface, combining multimodal embeddings to improve recommendation depth at scaleImplement query-time optimizations including caching, filtering, and index sharding strategiesTune vector quantization strategies (PQ, SQ, Binary Quantization) to reduce memory footprint and improve search throughput without compromising retrieval precisionOwn performance SLAs and monitor retrieval systems for latency, throughput, recall, and cost efficiencyBuild and maintain scalable batch and streaming pipelines, with logging, metrics, and alerting to surface anomalies and maintain observabilityProcess content at scale using distributed frameworks such as Spark or RayArchitect and build scalable integration layers on top of vector databases, exposing robust APIs and services for similarity search, hybrid retrieval, and metadata filteringOwn model versioning and embedding migration strategies, building compatibility tooling that prevents embedding drift from degrading retrieval quality across model upgradesCollaborate with backend and platform teams to ensure interoperability with upstream data pipelines and integration with downstream personalization and discovery surfacesCommunicate technical system behavior, tradeoffs, and recommendations clearly to both technical and non-technical stakeholdersMentor direct reports, providing technical guidance in multimodal ML, vector retrieval, and production systems designTake ownership of project outcomes from scoping through delivery in a dynamic environment, proactively identifying and mitigating risks across video processing, metadata, and indexing workflowsSkills5–8+ years of experience in machine learning engineering, with a focus on production ML systemsExpertise in multimodal ML, including experience with video, image, and/or audio embedding modelsDeep knowledge of vector embedding generation, storage and retrieval, with preference for hands-on Qdrant experience (FAISS, Pinecone, Pgvector, AlloyDB or similar also considered)Strong Python proficiency; Java is a plusDemonstrated experience building and operating data pipelines at scale, including batch and streaming ingestion workflowsSolid understanding of hybrid retrieval systems: vector search, lexical search, and rerankingProven ability to communicate technical concepts clearly and partner effectively with product and engineering teamsTrack record of mentoring engineers and leading technical decisions in a team settingExperience with agentic systems and multi-agent orchestrationKnowledge of Diversity & Relevance algorithms such as Maximal Marginal Relevance (MMR) within the re-ranking phaseBackground in video codecs, FFmpeg, or low-level video processing pipelinesAwareness with retrieval-augmented generation (RAG) systemsBenefitsMedicalDentalVision401(k) planLife insurance coverageDisability benefitsTuition assistance programPTOThis position is bonus eligible.Generous paid time off.Opportunities for both on-site and virtual engagement events.Unique opportunities to make meaningful connections and build a vibrant community, both inside and outside the workplace.Company OverviewParamount is a leading media and entertainment company that creates premium content and experiences for audiences worldwide. It was founded in 1914, and is headquartered in New York, New York, USA, with a workforce of 10001+ employees. Its website is https://www.paramount.com.Company H1B SponsorshipParamount has a track record of offering H1B sponsorships, with 2 in 2024. Please note that this does not guarantee sponsorship for this specific role.