TalentAQ

TalentAQ

Machine Learning Engineer

AI/ML•Full Time•4+ years•

Required Skills
16 skills

Python
SQL
GenAI
NLP
LLMs
scikit-learn
PyTorch
TensorFlow
HuggingFace
AWS
Azure
Docker
Git
Spark
Airflow
PySpark

Job Description

<p>We’re looking for a Machine Learning Engineer to join our Applied AI Lab and play a hands-on role in building intelligent, scalable, and production-ready ML systems. You’ll work at the intersection of rapid prototyping and product-focused ML, contributing to both short-cycle innovation and long-term platform stability.</p><p>If you enjoy wearing multiple hats, thrive in fast-paced environments, and are excited about shaping how AI transforms healthcare and life sciences, this opportunity is for you.</p><h3>Key Responsibilities</h3><ul><li>Solve business problems with cutting-edge AI solutions, focusing on cost-efficiency and reliability.</li><li>Collaborate with Lab leads, product designers, researchers, and architects to scope MVPs and define core capabilities.</li><li>Build modular, reusable components for GenAI solutions and traditional ML pipelines (training, evaluation, deployment).</li><li>Design and develop API-based AI tools and batch data transformation workflows.</li><li>Implement end-to-end solutions for batch and real-time algorithms, including monitoring, logging, automated testing, and performance evaluation.</li><li>Develop production-grade solutions following software engineering best practices.</li><li>Support experimentation, A/B testing, and fine-tuning cycles.</li><li>Stay updated on the latest advancements in Generative AI and related technologies.</li><li>Document architectures, processes, and technical decisions.</li></ul><h3>Qualifications</h3><ul><li>Bachelor’s/Master’s in Computer Science, Engineering, Data Science, or related field.</li><li>4.5+ years of experience as an AI/ML Engineer.</li><li>Strong knowledge of Python, SQL, and data processing languages.</li><li>Solid understanding of ML concepts (GenAI, NLP, LLMs).</li><li>Hands-on experience with open-source LLMs.</li><li>Proficiency in software engineering fundamentals (unit testing, modular design, CI/CD).</li><li>Strong experience with ML/AI frameworks (scikit-learn, PyTorch, TensorFlow, HuggingFace).</li><li>Familiarity with cloud platforms (AWS/Azure), containerization (Docker), and version control (Git).</li><li>Exposure to ETL tools (Spark, Airflow), PySpark, data modeling/warehousing, and CI/CD pipelines is a plus.</li><li>Experience with vector embeddings, multimodal data, agentic workflows, and LLM fine-tuning/RAG pipelines.</li><li>Exposure to healthcare/life sciences datasets (EHR, claims, clinical trials).</li><li>Prior experience in startup or R&D environments preferred.</li><li>Excellent communication and collaboration skills.</li></ul>

We’re looking for a Machine Learning Engineer to join our Applied AI Lab and play a hands-on role in building intelligent, scalable, and production-ready ML systems. You’ll work at the intersection of rapid prototyping and product-focused ML, contributing to both short-cycle innovation and long-term platform stability.

If you enjoy wearing multiple hats, thrive in fast-paced environments, and are excited about shaping how AI transforms healthcare and life sciences, this opportunity is for you.

Key Responsibilities

  • Solve business problems with cutting-edge AI solutions, focusing on cost-efficiency and reliability.
  • Collaborate with Lab leads, product designers, researchers, and architects to scope MVPs and define core capabilities.
  • Build modular, reusable components for GenAI solutions and traditional ML pipelines (training, evaluation, deployment).
  • Design and develop API-based AI tools and batch data transformation workflows.
  • Implement end-to-end solutions for batch and real-time algorithms, including monitoring, logging, automated testing, and performance evaluation.
  • Develop production-grade solutions following software engineering best practices.
  • Support experimentation, A/B testing, and fine-tuning cycles.
  • Stay updated on the latest advancements in Generative AI and related technologies.
  • Document architectures, processes, and technical decisions.

Qualifications

  • Bachelor’s/Master’s in Computer Science, Engineering, Data Science, or related field.
  • 4.5+ years of experience as an AI/ML Engineer.
  • Strong knowledge of Python, SQL, and data processing languages.
  • Solid understanding of ML concepts (GenAI, NLP, LLMs).
  • Hands-on experience with open-source LLMs.
  • Proficiency in software engineering fundamentals (unit testing, modular design, CI/CD).
  • Strong experience with ML/AI frameworks (scikit-learn, PyTorch, TensorFlow, HuggingFace).
  • Familiarity with cloud platforms (AWS/Azure), containerization (Docker), and version control (Git).
  • Exposure to ETL tools (Spark, Airflow), PySpark, data modeling/warehousing, and CI/CD pipelines is a plus.
  • Experience with vector embeddings, multimodal data, agentic workflows, and LLM fine-tuning/RAG pipelines.
  • Exposure to healthcare/life sciences datasets (EHR, claims, clinical trials).
  • Prior experience in startup or R&D environments preferred.
  • Excellent communication and collaboration skills.

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