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Proficiency in Python and relevant deep learning frameworks - both training (e.g. PyTorch, Tensorflow, JAX) and serving (e.g., Hugging Face TGI/Transformers/Adapters/outlines, vLLM) Strong software engineering skills with a track record of developing data-driven machine learning systems or products.
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PhD in applied mathematics, computer science, physics or other quantitative disciplines with a strong focus on machine learning and deep learning. Strong experience and knowhow to develop, innovate and leverage deep generative machine learning models for protein, RNA or small molecules therapeutics (representative examples include ProtVAE, MolMIM, MolGPT.
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This position is ideal for someone with deep expertise in machine learning, deep learning (particularly for building biologically meaningful representations of chemical structures), and computational chemistry, sciences and who is committed to building a high-preforming team.
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Develop, train, validate and test models (soft sensors) using machine learning and deep learning methods (classical and state of the art) applied for regression of time series sensor signals and/or image processing to monitor critical process parameters (CPP) and critical quality attributes (CQA) in production processes of therapeutic molecules.
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Extensive experience using machine learning and deep learning toolkits (e.g., TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas) Strong expertise in Machine Learning and Deep Learning with hands-on implementation experience, particularly with "noisy" real-world problems.
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Solid knowledge of machine learning and deep learning fundamentals with experience in one or more of computer vision, NLP, speech, reinforcement learning, generative models, etc.
Full-timeExpandApply NowActive JobUpdated 2 months ago - UpvoteDownvoteShare Job
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Distinct experience in advanced probability, statistics, machine learning, big data processing, analytics, and pipelining using Spark is essential, as well as experience in deep learning, generative AI, LLMs, and NLP. This role involves developing data science solutions, mentoring and imparting knowledge about machine learning and data concepts and techniques, as well as driving adoption of standards, processes, and tools to achieve high operational efficiency.
$242,000 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Strong understanding of machine learning algorithms, statistical modeling, and deep learning techniques. Lead Machine Learning Engineer – Semiconductor. Machine Learning | Semiconductor Manufacturing | AI | Electrical Engineering | Automation | MLOps | Java | C.
$200,000 a yearFull-timeExpandApply NowActive JobUpdated Yesterday - UpvoteDownvoteShare Job
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5-7 years experience across deep learning frameworks like Keras, TensorFlow or PyTorch and machine learning packages (sklearn, etc.) The ideal candidate has both a theoretical and practical understanding of deep learning techniques and has a proven track record in areas such as clinical research, computational biology, probability, statistics, or data science.
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Deep understanding of deep learning frameworks (e.g., PyTorch, PyTorch Lightning, JAX) and libraries (e.g., CUDA). We are seeking a skilled Principal Software Engineer to join our dynamic team of experts in developing cutting-edge machine learning systems for real-world applications.
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In this Director-level role, the fellow must possess extensive and comprehensive expertise in various machine learning methods, covering classical approaches (random forest, SVMs) and modern deep learning-based methods, with experience in translating theoretical algorithm development into practical and high performance implementations.
$282,000 a yearFull-timeExpandApply NowActive JobUpdated Today - UpvoteDownvoteShare Job
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6+ years overall experience (3+ post-Masters or PhD) as a machine learning engineer, software engineer, or applied scientist. Experience with state-of-the-art deep-learning techniques such as transformers, diffusion models, and multi-modal modeling, in domains such as robotics, computer vision, and NLP.
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M.S. degree or higher in Computer Science, Software Engineering, Data Science, Machine Learning/Deep Learning, Math, Physics or any related field. Strong background in machine learning algorithms and techniques, including supervised and unsupervised learning, deep learning, transformer, reinforcement learning, etc.
$305,300 a yearFull-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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10 + years of professional experience as a data scientist or machine learning engineer with proven track record of delivering functional product oriented ML solutions. Extensive experience with Python Machine Learning toolset (Tensorflow, PyTorch, Scikit-learn, Numpy, Pandas.
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Experience leveraging complex data to drive business decisions, hands-on experience in data science methodologies (predictive analytics, machine learning, patient level data triggers) using R, Python, Databricks and deep knowledge of Qlik, PowerBI, Tableau for visualization.
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