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Machine Learning Engineer (Mid-Level)

Remote: 
Full Remote
Experience: 
Mid-level (2-5 years)
Work from: 
Washington (USA)

Kaztronix LLC logo
Kaztronix LLC Human Resources, Staffing & Recruiting SME https://www.kaztronix.com/

Job description


Kaztronix has an exciting Remote opportunity with an outstanding organization. The Customer is on a mission to develop products and services for customers around the world to maximize their data. The candidates need to be eligible to work in the United States v
Machine Learning Engineer (Mid-Level)
Do you thrive on applying machine learning (Client) to solve real-world problems and build intelligent systems? Are you passionate about leveraging data to drive innovation and create impactful solutions?
. We are seeking a talented and motivated individual with a strong foundation in Client principles and proven experience in developing and deploying Client models.
In this role, you will:
  • Design and implement Client pipelines: Work closely with data scientists and engineers to understand business needs, select appropriate Client algorithms, and develop robust data pipelines for model training and deployment.
  • Train and optimize Client models: Utilize various Client techniques and tools to build, train, and evaluate high-performing models on diverse datasets. Fine-tune models for optimal performance and ensure generalizability.
  • Deploy and integrate Client models: Integrate trained models into production environments, ensuring scalability and reliability. Monitor model performance and proactively address any issues.
  • Collaborate with cross-functional teams: Work closely with data scientists, software engineers, and product managers to translate business requirements into technical solutions.
  • Stay current with the latest advancements: Continuously learn and explore new Client techniques and tools to ensure you are at the forefront of the field.
To be successful in this role, you should have:
  • 3+ years of experience as a machine learning engineer or a related field
  • Bachelor's Degree in Computer Science, Data Science or Machine Learning related field
  • Strong understanding of machine learning concepts, including supervised and unsupervised learning, deep learning, and large language models
  • Familiarity with common Client libraries and frameworks (e.g., TensorFlow, PyTorch, scikit-learn)
  • Experience with data preprocessing, feature engineering, and model evaluation
  • Proficiency in programming languages (i.e. Python)
  • Deep working with Client and data-driven environments and related technologies (i.e. , Vertex AI)
  • Deep experience with SQL, NoSQL databases (i.e. MySQL, MongoDB, BigQuery)
  • Good working knowledge of Cloud environments (i.e. AWS, GCP)
  • Understanding of container and container orchestration (i.e. Kubernetes, Docker)
  • Working knowledge with automation stacks (i.e Terraform)
  • Excellent problem-solving, debugging and analytical skills
  • Strong communication and collaboration skills
  • A passion for learning and staying up-to-date with the latest advancements in Data and Client.


Kaztronix is an equal opportunity employer and does not discriminate on the basis of race, color, national origin, sex, age, religion, disability, veteran status or any other consideration made unlawful by federal, state or local laws. In addition, all human resource actions in such areas as compensation, employee benefits, transfers, layoffs, training and development are to be administered objectively, without regard to race, color, religion, age, sex, national origin, disability, veteran status or any other consideration made unlawful by federal, state or local laws.

By applying to the position, you acknowledge that your information will be used by Kaztronix in processing your application.

Required profile

Experience

Level of experience: Mid-level (2-5 years)
Spoken language(s):
English
Check out the description to know which languages are mandatory.

Other Skills

  • Problem Solving
  • Analytical Skills
  • Verbal Communication Skills
  • Organizational Skills

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