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The qualified candidate for this position will lead TSL Developmental Test & Evaluation (DT&E) projects, Internal Research and Development (IRaD) projects, and other company divisions with machine learning and artificial intelligence expertise.
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Formal training in Biology, Computational Biology, Statistics, Machine Learning, or a related technical discipline. The ideal candidate should have an outstanding scientific reputation in the field of machine learning research for computational biology and a demonstrated passion for solving biological problems relevant to drug discovery.
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We are seeking an Applied Scientist to lead our forecasting initiatives, developing cutting-edge advertising products and technologies that impact billions in revenue and address complex challenges in infrastructure, algorithms, and machine learning.
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Data Architecture & Tools: modern cloud data platforms (Snowflake, Databricks, Big Query, RedShift), data analytics tools (Tableau, Looker, Power BI), data programming models (DataFrames, pandas), and AI (Python, R, Jupyter Notebooks, data wrangling, machine learning.
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Additionally, you will act as the post-sale technical lead for Data Cloud, leveraging your expertise and technical credibility to engage and communicate effectively at all levels within an organization.
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Salesforce Smart: Deep, technical knowledge of the Salesforce platform (Salesforce Admin and Advanced Admin level certifications, hands-on experience with Salesforce Clouds). Help ensure customer success by increasing focus and technical accountability to our most complex customers who need guidance to accelerate usage on Data Cloud workloads.
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Working in conjunction with the teams’ lead copywriter, lead designer, project manager, and digital content strategist, this person will write and edit copy for marketing materials supporting Connections Academy schools, internal organization communications and emerging B2B partnerships.
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Technical Expertise: Full-stack technical qualifications (CRM, Data Architecture, AI/ML) and experience managing technical relationships with C-Level executives. The Consumption Lead, Data Cloud, demonstrates deep business, industry, and product knowledge to partner with customers, guiding them to accelerate Data Cloud consumption and return on investment with Salesforce.
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The Consumption Lead, Data Cloud, works directly with customers that can vary in their market segment, size, solution complexity, and life cycle, all depending on the customer’s needs. Proactively communicate technical product changes, degradations, outages, end of life, and other relevant updates.
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As world leaders in digital technologies including IoT, Artificial Intelligence, Machine Learning, Robotic Process Automation, Chatbots, Block Chain and Cyber Security, Sonata s people and systems are nurtured to deliver on our commitment to excellence in business technology solutions.
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In addition, the candidate should have a strong understanding and experience with the integrated machine learning environments provided in Azure, AWS and GCP, along with emerging experience with Generative AI ML technical architectures that include pre-trained LLM and diffusion models such as LLaMA, ChatGPT, Gemini, Stability AI and Claude as well as Vector Databases and orchestration tools such as LangChain.
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Explore diverse ML technologies, expanding your technical expertise. Examples of the brands Conviva has helped innovate, adapt, and scale at unprecedented speed include: DAZN, Disney+, HBO, Hulu, NBCUniversal, Paramount+, Peacock, Sky, Sling TV, Univision and Warner Bros Discovery.
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Hands-on experience with machine learning (including deep learning and reinforcement learning), and one or more of the following technical areas: large language models (LLM), generative AI, decision science, human machine teaming, cognitive science, AI testing and evaluation, multi-agent systems, knowledge-based reasoning, automated planning, semantics, and ontologies.
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As a Senior Machine Learning Engineer, you will work on building AI/ML solutions across a wide range of business applications. Experience developing and deploying Machine Learning solutions on cloud platforms (e.g., AWS, Azure, or GCP.
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Design, develop and implement data science projects, including machine learning models, deep learning models, NLP solutions, statistical analysis, and data visualization. Strong knowledge of machine learning, deep learning, NLP, statistical analysis, and data visualization tools and technologies.
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machine learning technical lead jobs Company: Pricewaterhousecoopers Advisory Services Llc in Us
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