ML Engineer /Data Scientist Job Details | QualityAI

QualityAI is an AI-first quality engineering company helping enterprises deploy and scale complex systems with greater confidence. They are seeking an ML Engineer / Data Scientist to design and implement machine learning solutions that support product development and content enrichment, while collaborating with cross-functional teams to enhance data and ML pipelines.

Responsibilities:

• Evaluate, fine-tune, and maintain statistical and machine learning models used in run-time production environments, measuring and communicating performance improvements to stakeholders
• Partner with cross-functional teams to design and optimize AI/ML solutions that deliver new product capabilities and internal workflow improvements, using news articles, photos, videos, election results, and other news data
• Research, evaluate, and recommend models and methodologies across the AI/ML landscape, presenting recommended solutions to technical and non-technical stakeholders
• Identify and address gaps in model quality and performance metrics, synthesizing findings into clear, actionable recommendations
• Contribute to the design and enhancement of data and ML pipelines, including multimodal embedding generation and knowledge extraction, with a focus on accuracy, efficiency, and scalability
• Design user-centered solutions and search algorithms focused on quality and performance
• Stay current with emerging technologies and advances in NLP, machine learning, and data science, proactively surfacing opportunities for improvement
• Support the full model development lifecycle, from problem definition and prototyping through integration, deployment, monitoring, and iteration
• Communicate analysis and present findings clearly, adapting to a range of technical and business audiences

Requirements:

• Python (NumPy, Pandas, JSON at scale) — 3+ years of hands-on data science experience, comfortable with large-scale semi-structured data
• NLP & Transformer Models — entity recognition, disambiguation, semantic similarity, embedding-based retrieval, plus transformer experience for extraction, classification, summarization, and generation
• Hybrid Search/Retrieval (including ANN, BM25, Elasticsearch/OpenSearch) — hybrid search algorithms, retrieval pipelines, intent detection, query expansion, and relevance tuning
• Multimodal/Video Data processing at scale— experience working with language and multimodal models, multimodal embedding generation, and handling visuals/video as part of real-world data pipelines
• 3+ years of relevant data science experience, with strong proficiency in Python including NumPy, Pandas, and large-scale semi-structured JSON data
• Bachelor's degree in data science or computer science
• Experienced applying core machine learning methods including classification, clustering, regression, and ranking
• Hands-on experience with NLP techniques such as entity recognition, disambiguation, semantic similarity, and embedding-based retrieval
• Experience with transformer models for structured extraction, classification, summarization, and generation
• Experience with hybrid search algorithms, retrieval pipelines, intent detection, query expansion, and relevance tuning in Elasticsearch or OpenSearch
• Experience working with both language and multimodal models
• Experience and comfort working with real-world data, including text and visuals, at scale
• Familiar with ML engineering and ML Ops practices, with a track record of delivering runtime solutions
• Familiarity with cohort analysis, session segmentation, A/B testing, and confidence calibration
• Analytical and curious, with strong problem-solving skills and a practical focus on high-impact, cost-aware solutions
• Able to effectively manage multiple project deliverables simultaneously
• Comfortable being accountable for deliverables across the full product development lifecycle, from problem definition through launch and iteration
• An effective communicator who can tailor analysis and presentations to both technical and non-technical audiences
• Collaborative and empathetic, with a genuine focus on user impact and a desire to grow data literacy across the organization
• Advanced-level professional competency in written and spoken English
• Authorization to work in the United States for any employer
• Experience in news media or working with news as data strongly preferred
• Master's degree in data science or a related field
• Familiarity with graph data models and designing entity-relationship schemas
• Eagerness to learn the technical nuances of large-scale media operations and identify opportunities within evolving systems