Senior Machine Learning Engineer
Senior Machine Learning Engineer
Posted on :
20-12-2024
Employer Active
1 Vacancy
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Job Description
A Senior Machine Learning Engineer designs builds and implements advanced machine learning models and algorithms to solve complex business problems. The role involves collaboration with data scientists software engineers and stakeholders to create scalable AI/ML solutions that drive business value.
Roles and Responsibilities
1. Machine Learning Model Development:
- Design develop and implement machine learning models such as classification regression clustering and deep learning algorithms.
- Optimize model performance using techniques like hyperparameter tuning and feature engineering.
- Research and experiment with stateoftheart ML techniques and tools.
2. Data Preparation:
- Collaborate with data engineers to preprocess clean and transform large datasets for ML modeling.
- Perform exploratory data analysis (EDA) to uncover trends patterns and outliers.
- Work with structured unstructured and realtime data pipelines.
3. Deployment and Scalability:
- Deploy machine learning models to production environments using tools like Docker Kubernetes or MLFlow.
- Build APIs and integrate ML solutions with existing software systems.
- Ensure scalability reliability and performance of ML systems in production.
4. Collaboration and Mentorship:
- Collaborate with crossfunctional teams to identify ML opportunities and integrate solutions.
- Mentor junior data scientists and ML engineers providing guidance on best practices and problemsolving.
- Translate business requirements into technical specifications for ML projects.
5. Tools and Frameworks:
- Use frameworks like TensorFlow PyTorch Scikitlearn or XGBoost for model development.
- Leverage cloud platforms (AWS Azure GCP) for largescale machine learning workloads.
- Implement big data tools such as Spark Hadoop or Kafka for largescale data processing.
6. Monitoring and Maintenance:
- Continuously monitor the performance of deployed ML models and update them as necessary.
- Troubleshoot and resolve issues in production ML systems.
- Develop automated pipelines for retraining models based on new data.
7. Research and Innovation:
- Stay updated on the latest advancements in AI/ML including generative AI NLP and computer vision.
- Propose innovative solutions and proofofconcept projects to tackle business challenges.
Skills and Qualifications
- 5 years of experience in machine learning data science or related roles.
- Proficiency in Python R or Scala for ML development.
- Expertise in ML frameworks like TensorFlow PyTorch Keras or Scikitlearn.
- Strong knowledge of mathematics and statistics including linear algebra and probability.
- Experience with cloud services like AWS Sagemaker Google AI Platform or Azure ML.
- Familiarity with MLOps practices for CI/CD pipelines in machine learning.
- Proficiency in big data tools like Spark and databases like SQL NoSQL.
- Strong problemsolving skills and ability to communicate complex concepts clearly.
machine learning,hyperparameter tuning,kafka,feature engineering,spark,hadoop,learning,azure,r,data analysis,mlops,gcp,algorithms,scala,sql,nosql,pytorch,python,data science,keras,ml,tensorflow,scikit-learn,aws
Employment Type
Full Time
Key Skills
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