Machine Learning Engineer Job Description

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Job Brief

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We are seeking for a skilled Machine Learning Engineer to become part of our team! Your primary role will be to formulate and facilitate machine learning models, construct algorithms, and analyze data. You must also have outstanding statistics and programming abilities to execute this job effectively.

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Your responsibilities may include cooperating with software developers, data scientists, and other stakeholders to design scalable and efficient systems. You should demonstrate solid data science knowledge and experience in a relevant ML position to ensure success as a machine learning engineer.

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Roles and Responsibilities

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• Creating self-running machine learning systems and artificial intelligence (AI) software to automate prediction models.
• Establishing data science prototypes and using relevant machine learning algorithms and tools.
• Ensuring that algorithms produce reliable user results.
• Auto-tagging photos and text-to-speech translations transform unstructured data into usable information.
• Solving complex problems with multi-layered data sets and improving current machine learning tools and frameworks.
• Building ML algorithms to assess vast quantities of historical data to generate predictions.
• Running tests, conducting statistical analysis, and interpreting test findings are part of the job.
• Understanding business objectives and creating models to assist them in being accomplished, as well as measurements to track their success
• Managing available resources such as hardware, data, and employees in order to meet deadlines
• Analyzing and visualizing data to obtain a better knowledge of it, then discovering discrepancies in data distribution that may have an impact on performance when deploying the model in the real world.
• Specifying the preprocessing or feature engineering that will be performed on a given dataset.
• Finding discrepancies in data distribution that may have an impact on model performance in real-world scenarios.
• Designing machine learning algorithms to examine massive data sets and anticipate the future.
• Keeping up with machine learning breakthroughs in the industry.

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Requirements and Skills

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• Data structure comprehension, data modeling, and software architecture
• Expertise in arithmetic, probability, statistics, and algorithms
• Strong understanding of machine learning frameworks and libraries (e.g., Keras or PyTorch or sci-kit-learn)
• Excellent analytical and problem-solving abilities
• BSc in Computer Science, Mathematics, or a related discipline.
• Knowledge of ML frameworks, libraries, data structures, data modeling, and software design is required.
• Strong analytical, problem-solving, and teamwork abilities.
• Outstanding time management and organizing skills.
• Proficiency in Python and fundamental machine learning libraries such as sci-kit-learn and pandas
• Expertise in visualizing and manipulating large datasets
• Knowledge of Linux
• The ability to select hardware for running an ML model with the required latency.
• Skilled with large data frameworks such as Hadoop, Spark, Pig, Hive, and others.
• Knowledge of machine learning frameworks such as Theano, Tensorflow, Caffe, and others.
• Enthusiasm for statistics and mathematics, as well as strong communication abilities to convey complicated ideas and concepts in simple dialogues.

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Average Salary

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The salary of a Machine Learning engineer varies depending on the experience, geographical region, and organization. Machine Learning engineers' average salary in the United States is nearly $1,36,047 per year. In the United Kingdom, a Machine Learning engineer earns nearly £58190 per year, almost close to 30 Lakhs in India.

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Common Machine Learning Engineer Job Titles

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The most common careers in Machine Learning include the following roles.

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• Data Engineer-Machine Learning: They construct pipelines for collecting, cleaning, and preparing data for machine learning models and ensure the data is of high quality and properly stored.

• Data Mining Analyst: In charge of extracting, analyzing, and interpreting data sets to identify patterns and trends in the program.

• R Statistical Programmer: Responsible for developing and coding statistical programs, analyzing data sets, and creating visualizations to interpret the results.

• Deep Learning Engineer: In this role, engineers are required to Analyze large data sets, design and implement neural networks, and optimize their performance.

• Blockchain Developer: This role requires developers to implement software solutions on blockchain technology and build distributed ledger systems and other technologies.

• Natural Language Processing Engineer: Responsible for building natural language processing models, creating data processing pipelines, and developing algorithms to analyze text.

• Machine Learning Architect: In charge of designing and building systems to support Machine Learning models and algorithms.

• Machine Learning Consultant: Accountable for providing technical advice and guidance to organizations on Machine Learning solutions.

• Business Intelligence Analyst: Responsible for formulating data-driven strategies to improve business operations and processes

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