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Evening Machine Learning Engineer Biotech Jobs (NOW HIRING)

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Job Summary We are seeking a Machine Learning Engineer with strong expertise in machine learning model development, data engineering, and modern cloud-based analytics platforms. This role will focus ...

Machine Learning Engineer - AI Data Trainer * Location: Remote About the job At Alignerr, we partner with the world's leading AI research teams and labs to build and train cutting-edge AI models.

Machine Learning Engineer

CA · On-site

$75 - $89/hr

Machine Learning Engineer Pay Rate: $75-$89/hour Position Summary We are seeking a skilled Machine Learning Engineer (MLOps) to support the full lifecycle of machine learning models, including design ...

They are seeking a Machine Learning Engineer to build systems that analyze the performance of music promotions, providing actionable insights for creators and partners. Responsibilities : • ...

Machine Learning Engineer Position: Full time Location: Carlsbad office About Us: NTENT provides a Platform-as-a-Service (PaaS), allowing industry partners to customize, localize and integrate search ...

Machine Learning Engineer Location: Detroit, MI- Onsite Type: Full-time Security Clearance: No clearance required, must be clearable. The Machine Learning Engineer will be an essential member of the ...

Spotify is a leading music streaming platform, and they are seeking a Machine Learning Engineer to join their Music Promotion team. The role involves building systems to understand the performance of ...

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Evening Machine Learning Engineer Biotech information

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$31.5K

$128.8K

$193.5K

How much do evening machine learning engineer biotech jobs pay per year?

As of Jun 14, 2026, the average yearly pay for evening machine learning engineer biotech in the United States is $128,769.00, according to ZipRecruiter salary data. Most workers in this role earn between $101,500.00 and $155,000.00 per year, depending on experience, location, and employer.

What is the difference between Evening Machine Learning Engineer Biotech vs Evening Data Scientist Biotech?

AspectEvening Machine Learning Engineer BiotechEvening Data Scientist Biotech
Required CredentialsBachelor's or Master's in Computer Science, Data Science, or related fields; experience with ML frameworksBachelor's or Master's in Data Science, Statistics, or related fields; proficiency in data analysis tools
Work EnvironmentDeveloping ML models, coding, deploying algorithms in biotech settingsAnalyzing datasets, creating reports, interpreting data in biotech companies
Employer & Industry UsageBiotech firms, research labs, pharmaceutical companiesBiotech firms, research institutions, healthcare organizations

While both roles involve working with data in biotech, the Evening Machine Learning Engineer Biotech focuses on developing and deploying machine learning models, whereas the Evening Data Scientist Biotech emphasizes data analysis and interpretation. Both roles require strong technical skills and are integral to biotech innovation, but they differ in daily tasks and technical focus.

What cities are hiring for Evening Machine Learning Engineer Biotech jobs? Cities with the most Evening Machine Learning Engineer Biotech job openings:
What are the most commonly searched types of Machine Learning Engineer Biotech jobs? The most popular types of Machine Learning Engineer Biotech jobs are:
What states have the most Evening Machine Learning Engineer Biotech jobs? States with the most job openings for Evening Machine Learning Engineer Biotech jobs include:

Machine Learning Engineer

Purple Drive Technologies

Newark, NJ • On-site

Full-time

Retirement

Posted 14 days ago


Job description

Overview:
Role: Machine Learning Engineer
As a Machine Learning Engineer, you will play a critical role in designing, developing, and deploying advanced machine learning solutions that drive innovation and create measurable business value. You will collaborate closely with business stakeholders, data scientists, and cross-functional engineering teams to transform ideas into scalable, production-ready systems. This role requires both strong technical expertise and leadership ability to guide a small team and deliver impactful solutions.
Key Responsibilities
  • Lead and deliver machine learning projects from inception through production, building strong relationships with business partners and cross-functional teams.
  • Collaborate with business leaders and subject matter experts to define success criteria and optimize products, features, and models.
  • Partner with data scientists to design, implement, and train machine learning models.
  • Work with infrastructure teams to enhance architecture, scalability, stability, and performance of ML platforms.
  • Design and optimize data pipelines to support high-performance ML model training and inference.
  • Extend and customize machine learning libraries and frameworks for project-specific needs.
  • Define and implement model monitoring, governance, and operationalization processes for ML solutions.
  • Establish objectives and own the technical roadmap for ML platforms, ensuring delivery of results.
  • Define and promote standards of engineering and operational excellence for ML systems.
  • Apply architectural best practices in the delivery of data science and AI solutions.
Required Skills & Experience
  • Strong background in software engineering with proven experience as a Machine Learning Engineer.
  • Bachelor's degree in Computer Science, Computer Engineering, or related field; Master's preferred.
  • Advanced proficiency in Python, Java, and Scala with solid CS fundamentals (algorithms, data structures, multithreading).
  • Hands-on experience with Generative AI, LangChain, and RAG-based techniques.
  • Expertise in ML/DL libraries such as XGBoost, Scikit-learn, TensorFlow, and PyTorch.
  • Experience building and deploying ML solutions on public clouds (AWS, GCP).
  • Familiarity with ML platforms such as SageMaker, H2O, and DataRobot.
  • Strong knowledge of the ML lifecycle, including containerization, batch vs. real-time inference, and application security.
  • Proven track record in developing and deploying production-grade ML applications with cloud-based automation pipelines.
  • Experience working in Agile/Scrum environments with multiple stakeholders.
  • Excellent communication, collaboration, and problem-solving skills with thought leadership and innovative thinking.
Nice-to-Have
  • Experience with search platforms (e.g., Solr, Elasticsearch).
  • Hands-on experience building recommender systems.
  • Exposure to graph databases (e.g., Neo4j).
  • Familiarity with CI/CD tools (e.g., Jenkins).
  • Domain knowledge in Financial Services, Insurance, or 401K.
  • AWS Solutions Architect certification.