Machine Learning Engineer

2 weeks ago

United Kingdom Tiger Advisory Full time

Machine Learning Engineer

Location: Remote (UK-based, working UK hours or India-based, working India hours)

Job Type: Contract

Duration: 6+ months


Job Overview: We are seeking talented Machine Learning Engineers to join our dynamic team in the coming months. Whether you are just starting your career or have extensive experience, we have opportunities available at multiple levels of seniority. As a Machine Learning Engineer, you will be responsible for designing, developing, and implementing machine learning models and algorithms to solve complex problems and drive innovation. This is a remote position, and candidates should be based in the UK or India.


Key Responsibilities:

  • Develop and implement machine learning models and algorithms to solve complex problems.
  • Work closely with data scientists, engineers, and product teams to understand business requirements and translate them into technical solutions.
  • Optimize and fine-tune machine learning models for performance and scalability.
  • Stay up-to-date with the latest advancements in machine learning and artificial intelligence technologies.
  • Collaborate with cross-functional teams to integrate machine learning solutions into products and services.
  • Conduct research and experiments to evaluate the effectiveness of machine learning models.
  • Document processes, methodologies, and results.


Qualifications:


For 0-2 Years of Experience:

  • Bachelor’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Basic understanding of machine learning algorithms and techniques.
  • Experience with programming languages such as Python, R, or Java.
  • Familiarity with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong problem-solving skills and attention to detail.
  • Excellent communication and teamwork abilities.


For 2-5 Years of Experience:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Proven experience in developing and deploying machine learning models.
  • Proficiency in programming languages such as Python, R, or Java.
  • Hands-on experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of data preprocessing, feature engineering, and model evaluation.
  • Ability to work independently and in a team environment.
  • Strong analytical and problem-solving skills.


For 5-10 Years of Experience:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field.
  • Extensive experience in machine learning model development and deployment.
  • Advanced proficiency in programming languages such as Python, R, or Java.
  • In-depth knowledge of machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Experience in leading projects and mentoring junior engineers.
  • Strong understanding of big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Excellent problem-solving skills and the ability to handle complex technical challenges.
  • Strong communication and leadership skills.


For 10+ Years of Experience:

  • Bachelor’s or Master’s degree in Computer Science, Data Science, Engineering, or a related field. A Ph.D. is a plus.
  • Extensive experience and deep expertise in machine learning and artificial intelligence.
  • Proven track record of leading large-scale machine learning projects and teams.
  • Advanced proficiency in multiple programming languages (e.g., Python, R, Java).
  • Expertise in machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, scikit-learn).
  • Strong understanding of advanced machine learning concepts and techniques.
  • Experience with big data technologies and cloud platforms (e.g., AWS, Azure, Google Cloud).
  • Excellent leadership, strategic thinking, and problem-solving abilities.
  • Exceptional communication skills and the ability to influence stakeholders at all levels.

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