related field. Professional experience with collaborative software development. Deep understanding of Python. Familiarity with Linux, bash, and the command line. Experience with modern statistical machine learning and AI, including Numpy, Scipy, and Pandas. Ability to write logical, consistent, self-explanatory code. Understanding of software design patterns, SOLID and DRY principles. Experience with Git/GitHub and best practices. Knowledge of More ❯
Hands-on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming and database querying. Overall knowledge of the Software Development Life More ❯
South East London, England, United Kingdom Hybrid / WFH Options
Hartree Partners
a Data Science related role Proven depth in probability & inference (e.g., Bayesian updating, time-series/state-space models, extreme-value theory). Hands-on Python for numerical analysis (numpy, pandas, xarray, SciPy/PyMC/PyTorch, or similar). Experience validating models with historical data and communicating results to non-specialists. Exposure to real-time data engineering (Kafka, Airflow More ❯
Hands-on practical experience in system design, application development, testing, and operational stability. Proficient in coding in Python. Proficient in the use of basic data science libraries in Python (NumPy, pandas, scikit-learn, pyspark). Experience in developing, debugging, and maintaining code in a large corporate environment with modern programming languages and database querying languages. Overall knowledge of the Software More ❯
for interaction with the models Testing and documentation Requirements: Experienced Python developer Experience utilising machine learning libraries such as (in order of importance) TensorFlow, HuggingFace, scikit-learn, PyTorch, Pandas, NumPy, SciPy Experience with AWS (principally EC2, S3, SageMaker) or Azure/GCP equivalents Some experience of designing, developing and deploying scalable infrastructure (eg Apache Airflow, Luigi or other cluster management More ❯
machine learning (MLOps), using tools such as MLflow, AWS Sagemaker, and Azure Machine Learning Experience in relevant Data Manipulation, Machine Learning and Statistical Analysis coding packages (eg. in Python: NumPy, Scikit-Learn, Pandas, Matplotlib etc.) Strong skills in data exploration, cleansing, modelling and presentation Strong experience in testing data models and Machine Learning Models Strong experience in data presentation and More ❯
and frameworks such as RAG, LangChain, TensorFlow, and PyTorch. Exposure to LLMs from model families such as Anthropic, Meta, Amazon, and OpenAI. Familiarity with tools and packages like Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks. Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Proficiency in data pre-processing, data wrangling, and augmentation techniques. Experience More ❯
Responsibilities Design, develop, and deploy machine learning models to solve complex business problems. Collaborate with cross-functional teams to integrate ML models into production systems. Utilize PyTorch, Scikit-learn, NumPy, and Pandas for data analysis and model development. Develop and maintain APIs for model deployment and integration. Fine-tune large language models to enhance performance and accuracy. Apply deep learning … And Skills Formal training or certification on Data engineering concepts and applied experience cProven experience in building and deploying machine learning models. Hands-on experience with PyTorch, Scikit-learn, NumPy, and Pandas. Proficient in Python programming language and building APIs. Solid understanding of statistics and machine learning theory. Experience with deep learning architectures, including LSTMs and Transformers. Experience in fine More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯
