VetJobs
Sr Machine Learning Engineer - Thousand Oaks, CA
VetJobs, Newbury Park, California, us, 91319
Sr Machine Learning Engineer - Thousand Oaks, CA
In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. Roles & Responsibilities: Collaborate with data scientists to develop, train, and evaluate machine learning models. Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct A/B testing and experimentation to optimize model performance. Work closely with data scientists, engineers, and product teams to deliver ML solutions. Stay updated with the latest trends and advancements. Must-Have Skills: Solid foundation in machine learning algorithms and techniques Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow) Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills Ability to learn quickly Good communication and interpersonal skills Good-to-Have Skills: Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing Experience with data engineering and pipeline development Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Knowledge of NLP techniques for text analysis and sentiment analysis Experience in analyzing time-series data for forecasting and trend analysis What we expect of you: We are all different, yet we all use our unique contributions to serve patients. The professional we seek will have these qualifications. Basic Qualifications: Doctorate degree OR Master's degree and 2 years of Computer Science experience OR Bachelor's degree and 4 years of Computer Science experience OR Associate's degree and 8 years of Computer Science experience OR High school diploma / GED and 10 years of Computer Science experience Preferred Qualifications: Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus. Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. What you can expect from us: As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications. In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include: A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan Stock-based long-term incentives Award-winning time-off plans Flexible work models, including remote and hybrid work arrangements, where possible Salary Range 158,606.00 USD - 200,052.00 USD
In this vital role you will play a pivotal role in building and scaling our machine learning models from development to production. Your expertise in both machine learning and operations will be essential in creating efficient and reliable ML pipelines. Roles & Responsibilities: Collaborate with data scientists to develop, train, and evaluate machine learning models. Build and maintain MLOps pipelines, including data ingestion, feature engineering, model training, deployment, and monitoring. Leverage cloud platforms (AWS, GCP, Azure) for ML model development, training, and deployment. Implement DevOps/MLOps best practices to automate ML workflows and improve efficiency. Develop and implement monitoring systems to track model performance and identify issues. Conduct A/B testing and experimentation to optimize model performance. Work closely with data scientists, engineers, and product teams to deliver ML solutions. Stay updated with the latest trends and advancements. Must-Have Skills: Solid foundation in machine learning algorithms and techniques Experience in MLOps practices and tools (e.g., MLflow, Kubeflow, Airflow) Experience in DevOps tools (e.g., Docker, Kubernetes, CI/CD) Proficiency in Python and relevant ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn) Outstanding analytical and problem-solving skills Ability to learn quickly Good communication and interpersonal skills Good-to-Have Skills: Experience with big data technologies (e.g., Spark, Hadoop), and performance tuning in query and data processing Experience with data engineering and pipeline development Experience in statistical techniques and hypothesis testing, experience with regression analysis, clustering and classification Knowledge of NLP techniques for text analysis and sentiment analysis Experience in analyzing time-series data for forecasting and trend analysis What we expect of you: We are all different, yet we all use our unique contributions to serve patients. The professional we seek will have these qualifications. Basic Qualifications: Doctorate degree OR Master's degree and 2 years of Computer Science experience OR Bachelor's degree and 4 years of Computer Science experience OR Associate's degree and 8 years of Computer Science experience OR High school diploma / GED and 10 years of Computer Science experience Preferred Qualifications: Certifications on GenAI/ML platforms (AWS AI, Azure AI Engineer, Google Cloud ML, etc.) are a plus. Excellent analytical and troubleshooting skills. Strong verbal and written communication skills Ability to work effectively with global, virtual teams High degree of initiative and self-motivation. Ability to manage multiple priorities successfully. Team-oriented, with a focus on achieving team goals. Ability to learn quickly, be organized and detail oriented. Strong presentation and public speaking skills. What you can expect from us: As we work to develop treatments that take care of others, we also work to care for your professional and personal growth and well-being. From our competitive benefits to our collaborative culture, we'll support your journey every step of the way. The expected annual salary range for this role in the U.S. (excluding Puerto Rico) is posted. Actual salary will vary based on several factors including but not limited to, relevant skills, experience, and qualifications. In addition to the base salary, Amgen offers a Total Rewards Plan, based on eligibility, comprising of health and welfare plans for staff and eligible dependents, financial plans with opportunities to save towards retirement or other goals, work/life balance, and career development opportunities that may include: A comprehensive employee benefits package, including a Retirement and Savings Plan with generous company contributions, group medical, dental and vision coverage, life and disability insurance, and flexible spending accounts A discretionary annual bonus program, or for field sales representatives, a sales-based incentive plan Stock-based long-term incentives Award-winning time-off plans Flexible work models, including remote and hybrid work arrangements, where possible Salary Range 158,606.00 USD - 200,052.00 USD