Infotree Global Solutions

Machine Learning Engineer

⭐ - Featured Role | Apply direct with Data Freelance Hub
This role is for a Machine Learning Engineer in Seattle, WA, with a contract length of unspecified duration and a competitive pay rate. Key skills include Python, ML lifecycle, big data, and experience with NLP and ML frameworks. A B.S. or M.S. in a related field is required.
🌎 - Country
United States
💱 - Currency
$ USD
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💰 - Day rate
Unknown
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🗓️ - Date
February 25, 2026
🕒 - Duration
Unknown
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🏝️ - Location
On-site
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📄 - Contract
Unknown
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🔒 - Security
Unknown
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📍 - Location detailed
Seattle, WA
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🧠 - Skills detailed
#Deep Learning #"ETL (Extract #Transform #Load)" #Automation #Statistics #Scala #PyTorch #Spark (Apache Spark) #ML (Machine Learning) #Automatic Speech Recognition (ASR) #Python #Computer Science #Data Processing #Deployment #Cloud #NLP (Natural Language Processing) #TensorFlow #Big Data
Role description
Position Title: Machine Learning Engineer Location: Seattle, WA 98109 Qualifications • Strong machine learning expertise with hands-on experience in model fine-tuning, evaluation, experiment tracking, pipeline building and deployment • 3+ years working experience in ML lifecycle, Model management, big data/Spark/MapReduce, large distributed system, cloud computing etc • Proficient coding skills in Python and experience with ML infrastructure tools • Excellent communication and problem-solving skills • Experience with LLMs, neural machine translation is a plus • Deep knowledge in ML frameworks and technologies such as NLP, MT, ASR, PyTorch, TensorFlow, JAX, and transformer architectures is a plus Description • You will be part of a team that's responsible for a wide variety of language technologies related development activities. Your focus will be on developing the model automation pipelines which are highly scalable, robust and efficient. The role will be part of the model automation team to deal with large quantities of data, apply the state-of-the-art methods in deep learning to tackle real world problems, create the production quality models at scale and set up ML CI/CD pipelines. Key responsibilities include: • Developing automation pipelines and tools for training, evaluating and deploying machine learning models for machine translation and related NLP tasks • Implementing and optimizing ML pipelines with emphasis on distributed data processing, training and efficiency • Collaborating with software engineers and QE to integrate ML models into production systems Education • B.S. or M.S. in Computer Science, Machine Learning, Statistics, or related field.