1 to 25 of 43 Remote/Hybrid Amazon SageMaker Jobs

large and complex datasets to solve high impact, customer facing product problems• Design, build, train, and deploy machine learning models using AWS services, with Amazon SageMaker as the core ML platform• Develop and productionise recommendation and personalisation systems used at scale• Own the full model lifecycle including experimentation … product or customer focused environment• Strong Python and SQL skills• Hands on, production experience using AWS for machine learning workloads• Strong experience with Amazon SageMaker for model training, deployment, and monitoring• Experience building and deploying machine learning models into live products• Solid understanding of applied machine learning techniques ...

Awareness of ethical, privacy, security and policy considerations in applied AI Desirable Experience Hands-on experience with AWS services such as Lambda, ECS, S3, SageMaker or Bedrock Knowledge of ML engineering and MLOps practices (e.g. Docker, MLflow) Experience working in government, defence or other highly regulated environments Proven application ...

data science roles (senior level). Hands-on experience with Python ML frameworks (scikit-learn, PyTorch, TensorFlow, XGBoost). Experience with AWS ML services (SageMaker, Lambda, S3) and MLOps/LLMOps tooling (MLflow, Weights & Biases, DVC). Proven track record transitioning models from experimentation to production with governance ...

experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation, A/B testing, and statistical evaluation. Proven track record transitioning models from ...

engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases ...

technical concepts to diverse audiences. Eligible for DV security clearance; sponsorship cannot be provided. Desirable: Knowledge of AWS services (e.g., Lambda, ECS, Bedrock, S3, SageMaker). Experience with ML engineering and MLOps (e.g., Docker, MLflow). Experience in regulated industries or government-related projects. Applying LLMs or advanced ...

Libraries: XGBoost, SKlearn, Tensorflow or PyTorch. In depth experience building solutions using public clouds such as AWS, GCP. Experience using ML platforms like SageMaker, H2O, DataRobot, etc. Strong knowledge on ML model development life cycle components like containers, batch vs real time inference endpoints, application security testing etc. Experience ...

deployment strategies. Strong communication skills and experience mentoring or leading technical initiatives. Nice to Have Experience with MLOps tools (MLflow, Kubeflow, SageMaker, Vertex AI). Familiarity with containerization and orchestration (Docker, Kubernetes). Experience working with large-scale datasets or real-time ML systems. Why Join Us Ownership ...

have: Strong Python ML experience (e.g. scikit-learn, XGBoost, PyTorch, or TensorFlow) Production experience with AWS ML services (e.g. SageMaker, Lambda, S3) Proven ability to move models from experimentation into live systems Experience with MLOps tools (MLflow, Weights & Biases, DVC, or similar) Hands-on exposure to LLM/GenAI ...

scikit-learn, PyTorch, transformers) Experience deploying models and working with cloud platforms (AWS preferred) Ability to communicate complex technical concepts clearly Desirable AWS services (SageMaker, ECS, Lambda, S3, Bedrock) MLOps/ML engineering experience (Docker, MLflow) Experience in government or regulated environments Practical experience applying LLMs Security Clearance UKIC ...

Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow, or Apache Beam . Background in front ...

PyTorch Experience with containerization tools like Docker and orchestration tools like Airflow or Astronomer Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI) Experience with CI/CD pipelines and automation tools such as GitHub Actions Understanding of monitoring and logging tools (e.g., NewRelic, Grafana ...

PyTorch Experience with containerization tools like Docker and orchestration tools like Airflow or Astronomer Familiarity with cloud platforms (AWS, Azure) and ML services (e.g., SageMaker, Vertex AI) Experience with CI/CD pipelines and automation tools such as GitHub Actions Understanding of monitoring and logging tools (e.g., NewRelic, Grafana ...

Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company ...

technical stakeholders Mentor junior team members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation ...

/CD pipelines, IaC, monitoring systems to ensure scalable, reliable data workflows. AWS data tooling such as S3/Glue/Redshift/SageMaker (Or relevant experience in another cloud technology). Familiarity with Docker/ec2, Terraform and CI/CD platform (Github Actions & Admin). Strong Data ...

engineering with GitHub Actions and/or Argo CD. Preferred/Bonus Research experience in edge AI or constrained/offline deployments. MLOps experience (Sagemaker, Kubeflow, ZenML). Experience building RESTful services around AI pipelines. ISO 27001, NIST SSDF, OWASP SAMM, or GDPR compliance literacy. Experience with AWS Karpenter ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...

within financial services, banking, or retail. 4+ years hands-on experience with data science and statistical tools such as Python, SPARK, Data Lake, AWS SageMaker, H2O, and SAS. 4+ years of machine learning experience, including handling large datasets and trend analysis. 4+ years applying US regulatory requirements for Model ...