Note: The job is a remote job and is open to candidates in USA. MNJ SOFTWARE is looking for talented individuals to join their team as a Machine Learning Engineer. In this role, you will participate in the design, development, and implementation of architectural deliverables for custom projects and products, working closely with various stakeholders to ensure successful project execution.

Responsibilities

• Work with Data Scientists and Business Analysts to frame problems in a business context
• Assist all the processes from data Collection, Cleaning and Preprocessing to training models and deploying them to production
• Understand Business Objectives and Developing models that help to achieve them, along with metrics to track their progress
• Explore and visualize data to gain an understanding of it, then identify differences in data distribution that could affect performance when deploying the model in the real world
• Define validation Strategies, Preprocess or Feature engineering to be done on a given Dataset and Data augmentation pipelines
• Analyze the errors of the model and design strategies to overcome them
• Collaborate with data engineers to build data and model pipelines
• Manage the Infrastructure and Data pipelines needed to bring code to production and demonstrate end-to-end understanding of applications (Including, but not limited to, the machine learning algorithms) being created

Skills

• Experience: 3-6 yrs
• Languages: English is the working language of this above stated post. Fluency in oral and written English is required
• Qualification: ME/M.TECH/BE/B.TECH/MCA/M.Sc(IT) etc
• Understanding of data structures, data modeling and software architecture
• Deep knowledge of Math, Probability, Statistics and Algorithms
• Experience with machine learning platforms such as Microsoft Azure, Google Cloud, IBM Watson and Amazon
• Big Data Environment: Hadoop, Spark
• Programming Languages: Python, R, PySpark
• Supervised & Unsupervised Machine Learning: Linear Regression, Logistic Regression, K-means Clustering, Ensemble Models, Random Forest, SVM, Gradient Boosting
• Sampling Data: Bagging & Boosting, Bootstrapping
• Experience of machine learning Algorithms and Libraries
• Must be Analytical and possess good problem-solving capabilities
• Independent thinker
• Certification: Optional

Benefits

• Reimbursement: Best in Industry
• Remote (Work From Home)
• Full time [Monday – Friday]
• Employees are required to have flexibility to work any of our 9-hour shift schedules during our normal business hours of (6am - 10pm IST) or (6pm to 6am IST). It may be necessary, given the business need, to work occasional overtime [unpaid].

Company Overview