ML Engineer_LRL Tech

Key Skills

Google Cloud Platform (GCP), JavaScript, Keras software library, PyTorch, Scikit-learn, Spark-SQL, TensorFlow

Job Description

Responsibilities:

• Develop and implement machine learning models and algorithms to solve specific business problems, such as predictive analytics, recommendation systems, or natural language processing.
• Collect, clean, and pre-process large datasets to extract relevant features and prepare them for machine learning tasks.
• Collaborate with data scientists and domain experts to understand business requirements and translate them into machine learning solutions.
• Experiment with different machine learning techniques and algorithms to optimize model performance and accuracy.
• Train and fine-tune machine learning models using a variety of methods, such as supervised learning, unsupervised learning, or reinforcement learning.
• Evaluate and validate the performance of machine learning models using appropriate metrics and statistical analysis.
• Deploy machine learning models into production environments, ensuring scalability, reliability, and performance.
• Collaborate with software engineers to integrate machine learning models into existing systems or develop new applications.
• Monitor and maintain deployed models, performing regular performance checks, debugging, and optimization as necessary.
• Stay updated with the latest advancements in machine learning and related fields, and apply them to improve existing models and processes.
• Document and communicate machine learning solutions, including code, methodologies, and results, to technical and non-technical stakeholders.

Essential Skills:

• Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field.
• Strong knowledge of machine learning algorithms and techniques, such as regression, classification, clustering, deep learning, and reinforcement learning.
• Proficiency in programming languages commonly used in machine learning, such as Python, R, or Java.
• Experience with machine learning libraries and frameworks, such as TensorFlow, PyTorch, scikit-learn, or Keras.
• Solid understanding of data manipulation and pre-processing techniques, including feature extraction, dimensionality reduction, and data normalization.
• Familiarity with big data processing tools and frameworks, such as Hadoop, Spark, or Apache Flink.
• Experience with cloud platforms and services, such as AWS, Azure, or Google Cloud, for scalable machine learning deployments.
• Proficient in using version control systems (e.g., Git) and collaborative software development practices.
• Strong analytical and problem-solving skills, with the ability to analyse complex datasets and derive actionable insights.
• Excellent communication skills to effectively collaborate with cross-functional teams and present technical concepts to non-technical stakeholders.
• Ability to work independently and manage multiple projects with competing deadlines

Desired Skills:

• Knowledge of distributed computing and parallel processing frameworks, such as MapReduce or Apache Spark.
• Familiarity with data visualization tools, such as Tableau, matplotlib, or ggplot.
• Understanding of natural language processing (NLP) techniques and frameworks, such as NLTK, SpaCy, or BERT.
• Experience with containerization technologies like Docker and orchestration tools like Kubernetes.
• Knowledge of software engineering principles and practices, including software design patterns and testing frameworks.

Eli Lilly and Company, Lilly USA, LLC and our wholly owned subsidiaries (collectively “Lilly”) are committed to help individuals with disabilities to participate in the workforce and ensure equal opportunity to compete for jobs. If you require an accommodation to submit a resume for positions at Lilly, please email Lilly Human Resources ( Lilly_Recruiting_Compliance@lists.lilly.com ) for further assistance. Please note This email address is intended for use only to request an accommodation as part of the application process. Any other correspondence will not receive a response.

Lilly does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status.