101 to 125 of 170 Permanent NumPy Jobs

DC/Northern Virginia with occasional travel to client sites. A degree in Computer Science or a related field. 3+ years of hands-on experience with Python coding (pandas, numpy, sklearn, TensorFlow, PyTorch, etc.). Proven experience deploying machine learning models into production environments. Proficiency with SQL/NoSQL databases, version control tools (e.g., Git), Docker, and Kubernetes. Strong ownership More ❯

again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong communication skills and a More ❯

pick up new skills quickly and to be able to work in a fast-moving, demanding environment. What you will be working with: Python, Jira, Selenium (Web Driver), Geist, NumPy, SQL, HTML, CSS, XML alongside helping to implement continuous delivery. More ❯

a cross-functional environment with other data scientists, software engineers, and T&L domain experts Your professional experience Essential: Expert Python programmer proficient in frameworks/libraries such as: Numpy, Pandas, Scikit-Learn, Langchain, Llamaindex, Azure AI Foundry, among others Practical experience and deep expertise with GenAI techniques such as Finetuning, Prompt engineering, prompt orchestration, retrieval methods (RAG and Knowledge More ❯

better Ideally experience with de novo transcriptome assembly, Machine Learning and/or Artificial Intelligence, or experience mining genomic data Experience with Python and libraries such as SciPy, Pytorch, NumPy, Pandas etc. What Next? If you'd like to hear more about this exciting Bioinformatician position, just give me a call or drop me an email, I'd love to More ❯

in Computer Science (or related field). 3+ years of experience writing production-grade Python code. 3+ years of hands-on experience with core Python data libraries (e.g., pandas, numpy, sklearn, tensorflow, pytorch, matplotlib). At least 1 year of experience deploying machine learning models in production environments. 1-2 years of experience working with SQL/NoSQL databases (e.g. More ❯

level experience in data science or a quantitative academic field. Strong programming skills, with the ability to quickly become fluent in Python. Deep knowledge of core data science libraries (NumPy, Pandas, Scikit-Learn) and at least one deep learning framework (TensorFlow, PyTorch, or similar). High mathematical and statistical competence, with the ability to design new algorithms when needed. Experience More ❯

Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and More ❯

Requirements: 5+ years of experience applying data science in commercial settings Proven ability to lead data science projects from concept to production Strong Python skills (including libraries like Pandas, NumPy, Scikit-learn); experience with other languages is a plus Deep understanding of statistical modelling, predictive analytics, and optimisation techniques Comfortable working with cross-functional teams, including engineers, product leads, and More ❯

precise targeting. Behavioral Logic: Develop complex mission logic, tactical decisions, and targeting sequences using Behavior Trees. Prototyping & Simulation: Rapidly prototype, simulate, and validate algorithms using Python and scientific libraries (NumPy, SciPy, Matplotlib). System Integration: Integrate, test, and deploy GNC software on hardware-in-the-loop (HIL) testbeds and flight hardware with PX4 autopilot stack. Performance Analysis: Analyze simulation and More ❯

quantitative academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all More ❯

the use and distribution of electrical energy) to secondary education minimum. - The ability to code in Python working with large datasets as a minimum. Familiarity with standard Python packages (NumPy/Pandas/Scikit-learn etc.) and some knowledge of VBA and SQL would also be preferable. - Competent user of specific Azure data related resources (or similar) including: Databricks and More ❯

models and vision and/or language, incl. local deployment of open models, continued training and fine-tuning cloud and local models Python and associated ML tools/frameworks (numpy, scipy, sklearn, pytorch) Experience with working collaboratively with other developers, following a flexible/agile/lean approach EPIC JOB + EPIC BENEFITS = EPIC LIFE We pay 100% for benefits More ❯

quantitative academic field Strong python programming skills as evidenced by earlier work in data science or software engineering. An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all More ❯

are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g. More ❯

are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g. More ❯

are looking for individuals who have working experience in or are comfortable supporting (or willing to learn) in the following areas: Programming for Data Science (e.g., Python with Pandas, NumPy, R) Statistical Analysis and Hypothesis Testing Data Cleaning, Preprocessing, and Feature Engineering Data Visualization (e.g., Matplotlib, Seaborn, Plotly, Tableau) Machine Learning Fundamentals (e.g., Supervised, Unsupervised Learning) Machine Learning Algorithms (e.g. More ❯

with strong understanding of RAG workflows, including indexing, retrieval, and integration with language models. Technical Proficiency : Advanced proficiency in Python and experience with data manipulation and analysis libraries (Pandas, NumPy, SciPy), along with strong knowledge of machine learning algorithms, statistical modelling, and data mining techniques. Commercial Acumen : Deep understanding of product dynamics, market needs, and commercial considerations essential for conceptualising More ❯

is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all More ❯

is not important, we do require the ability to become a fluent Python programmer in a short timeframe An excellent command of the basic libraries for data science (e.g. NumPy, Pandas, Scikit-Learn) and familiarity with a deep-learning framework (e.g. TensorFlow, PyTorch, Caffe) A high level of mathematical competence and proficiency in statistics A solid grasp of essentially all More ❯

vice versa. Proven experience of change management skills. Core technical skills: Strong knowledge of data science fundamentals (Machine Learning methods, Statistics). Fluent in common analytics tools (Python, Pandas, Numpy, ScikitLearn, SQL, etc.) Comfortable to use data visualization libraries (e.g. Seaborn, Matplotlib) Demonstrated initiative, judgment and discretion while handling sensitive information Preferred Qualifications: If you have the following characteristics, it More ❯

data analytics/scientists on the development of analytics, insight and marketing model development. Data manipulation, cleaning and analysis : Proficient in data manipulation and analysis using tools like Pandas, NumPy, and SQL. Ability to work with large-scale datasets and extract meaningful insights. Experience in data processing to enable accurate analytics as well as effective model creation. Ability to handle More ❯

data analytics/scientists on the development of analytics, insight and marketing model development. Data manipulation, cleaning and analysis : Proficient in data manipulation and analysis using tools like Pandas, NumPy, and SQL. Ability to work with large-scale datasets and extract meaningful insights. Experience in data processing to enable accurate analytics as well as effective model creation Ability to handle More ❯

model deployment and beyond (monitoring and improvement). In-depth knowledge of statistical hypothesis testing and ML modeling techniques. Experience in using Python for numerical/statistical programming (including Numpy, Pandas, and Scikit-learn). Significant experience in using SQL. Ability to communicate effectively with audiences of various backgrounds, levels, and functions. Experience in conducting and analyzing AB tests in More ❯

data structures and software engineering fundamentals BS in Robotics, Computer Science, Mechatronics, Mathematics, Mechanical Engineering, or related field Strong DNN/ML background and experience in standard domain libraries (numpy, opencv, pytorch, etc) Strong C++ or Rust experience Experience deploying to real-time robotics systems Eligible to obtain and maintain an active UK Security Clearance PREFERRED QUALIFICATIONS Experience processing sensor More ❯