Machine Learning Engineer
Role: Machine Learning Engineer
Location: Atlanta,GA (Onsite)
Duration: 6+ Months
Job Description:
We're seeking a highly skilled Machine Learning Engineer to design, develop, and deploy machine learning models and algorithms that drive business value. The successful candidate will work closely with cross-functional teams to identify opportunities, develop solutions, and implement scalable and efficient ML models.
Responsibilities:
1. Design and Development: Design, develop, and deploy machine learning models and algorithms using techniques such as deep learning, natural language processing, and computer vision.
2. Data Preprocessing: Collect, preprocess, and analyse large datasets to train and validate ML models.
3. Model Evaluation: Evaluate and optimise ML model performance, ensuring they meet business requirements and are scalable.
4. Collaboration: Work closely with data scientists, product managers, and engineers to identify opportunities, develop solutions, and implement ML models.
5. Deployment: Deploy ML models in production environments, ensuring they are efficient, scalable, and reliable.
Requirements:
1. Technical Skills: Proficiency in programming languages such as Python, R, or Julia, and experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn.
2. Machine Learning: Strong understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and natural language processing.
3. Data Preprocessing: Experience with data preprocessing, feature engineering, and data visualisation.
4. Communication: Excellent communication and collaboration skills, with the ability to explain complex technical concepts to non-technical stakeholders.
5. Problem-Solving: Strong problem-solving skills, with the ability to think creatively and develop innovative solutions.
Nice to Have:
1. Cloud Experience: Experience with cloud platforms like AWS, Azure, or Google Cloud.
2. DevOps: Familiarity with DevOps tools like Docker, Kubernetes, or Jenkins.
3. Domain Expertise: Domain expertise in areas like computer vision, natural language processing, or recommender systems.
Education:
1. Bachelor's or Master's Degree: Degree in Computer Science, Electrical Engineering, Statistics, or a related field.