MACHINE LEARNING ENGINEER

Johnson & Johnson is recruiting for a Machine Learning Engineer, located in Manila, Philippines.
We are currently seeking an individual with strong expertise and experience in machine learning to join our dynamic team.
As a Machine Learning Engineer, you will actively participate in designing, developing, and deploying machine learning models and algorithms.
You will collaborate closely with our data scientists, software engineers, and multidisciplinary teams to facilitate the development and implementation of machine learning solutions that will positively impact the company's success.
Key Responsibilities.
Collaborate with data scientists and data developers to understand project requirements and define the scope of machine learning projects.
Develop and implement machine learning models and algorithms that address sophisticated business problems and improve decision-making processes.
Clean, preprocess, and analyze large datasets to ensure data quality and suitability for machine learning tasks.
Perform feature engineering and feature selection to optimize model performance.
Train, evaluate, and fine-tune machine learning models using various algorithms and techniques.
Deploy machine learning models into production systems and ensure their scalability and robustness.
Monitor and maintain deployed models to assess performance and address any potential issues or updates.
Stay updated with the latest advancements in machine learning and artificial intelligence and propose innovative ideas for improvement and growth.
Qualifications Education.
Bachelor's degree in Computer Science, Statistics, Engineering, or a related field, or equivalent experience.
A Master's or Ph.
.
degree in a relevant field is a plus.
Experience and Skills.
Required.
Experience as a Machine Learning Engineer or in a similar role, with a track record of successful machine learning projects.
Experience in DataLakehouse and Large Language Models.
Strong programming skills in languages such as Python, R, or Java, along with proficiency in using libraries and frameworks such as TensorFlow, PyTorch, or Scikit-learn.
Solid understanding of machine learning concepts and algorithms, including supervised and unsupervised learning, deep learning, and reinforcement learning.
Experience with data preprocessing, feature engineering, and data visualization techniques.
Proficiency in working with large datasets and using SQL and/or NoSQL databases.
Familiarity with cloud platforms such as Amazon Web Services (AWS) or Google Cloud Platform (GCP) for efficient model deployment and scaling.
Excellent problem-solving skills and ability to analyze complex data and translate it into actionable insights.
Effective collaboration with diverse teams and concise presentation of findings is crucial.
Preferred.
Master's or Ph.
.
degree in Computer Science, Engineering, or a related field.
Experience with natural language processing (NLP) and computer vision.
Knowledge of distributed computing frameworks such as Apache Spark, Databricks, Domino, Snowflake and the like.
Experience with containerization technologies such as Docker and Kubernetes.
Familiarity with version control systems and collaborative development tools (e.
., Git, Jira).
Publications or contributions to the machine learning community.
Knowledge to develop front-end deployment visualization tools.
Other.
Proficiency in English is required.
Relevant certifications, such as AWS Certified Machine Learning - Specialty or Google Cloud Certified - Professional Data Engineer, are preferred.