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Machine Learning Engineer Job Opening In Indianapolis – Now Hiring Elanco


Job description


At Elanco (NYSE: ELAN) – it all starts with animals!
As a global leader in animal health, we are dedicated to innovation and delivering products and services to prevent and treat disease in farm animals and pets.

At Elanco, we are driven by our vision of Food and Companionship Enriching Life and our purpose – all to Go Beyond for Animals, Customers, Society and Our People.
At Elanco, we pride ourselves on fostering a diverse and inclusive work environment.

We believe that diversity is the driving force behind innovation, creativity, and overall business success.

Here, you’ll be part of a company that values and champions new ways of thinking, work with dynamic individuals, and acquire new skills and experiences that will propel your career to new heights.
Making animals’ lives better makes life better – join our team today!
Your Role:
As a Machine Learning (ML) Engineer at Elanco, you will be a key member of our engineering team, specializing in the end-to-end lifecycle of custom and third-party (including open source) machine learning models.

You will translate complex business problems into scalable, production-ready AI solutions.

This role is focused on the practical application of machine learning, requiring a strong blend of software engineering discipline and deep ML expertise to design, build, and deploy models that deliver real-world value.
This includes four strategic priorities:
* Pipeline Acceleration: Optimize the search and approval of high impact medicines with a focus on speed, cost and precision.
* Manufacturing Excellence: Improve the efficiency, quality and consistency of core manufacturing processes, specifically execution and equipment effectiveness.
* Sales Effectiveness: Simplify the process to find, trust and consume relevant customer insights that drive sales growth and improved engagement.
* Productivity: Expand operating margin through efficiency by systematically reducing our operating expenses across the company, improving profitability.
Your Role:
* Custom Model Development: Design, build, and train bespoke ML models tailored to specific business needs, from initial prototype to full implementation.
* Third-Party Model Utilization: Identify, tune and deploy third-party ML models, covering proprietary and open-source models.
* Production Deployment: Manage the deployment of ML models into our production environments, ensuring they are scalable, reliable, and performant.
* MLOps and Automation: Build and maintain robust MLOps pipelines for Continuous Integration/Continuous Delivery (CI/CD), model monitoring, and automated retraining.
* Data Pipeline Construction: Collaborate with data engineers/stewards to build and optimize data pipelines that feed ML models, ensuring data quality and efficient processing for both training and inference.
* Cross-Functional Collaboration: Work closely with data scientists, product managers, and software engineers to define requirements, integrate models into applications, and deliver impactful features.
* Code and System Quality: Write clean, maintainable, and well-tested production-grade code.

Uphold high software engineering standards across all projects.
* Performance Tuning: Monitor and analyze model performance in production, identifying opportunities for optimization and iteration.
What You Need to Succeed (Minimum Qualifications):
* Education: A Bachelor’s or Master’s degree in Computer Science, Software Engineering, Artificial Intelligence, or a related quantitative field.
* Required Experience: 3+ years experience in Machine Learning/Engineer or relevant work.
* Programming Excellence: Advanced proficiency in Python and deep experience with core ML/data science libraries (e.g., PyTorch, TensorFlow, scikit-learn, pandas, NumPy).
* Software Engineering Fundamentals: Strong foundation in software engineering principles, including data structures, algorithms, testing, and version control (Git).
* ML Model Deployment: Proven, hands-on experience deploying machine learning models into a production environment.
* MLOps Tooling: Experience with MLOps tools and frameworks and containerization technologies (Docker, Kubernetes).
* Cloud Platform Proficiency: Practical experience with Public Cloud, specifically Microsoft Azure and Google Cloud Platform (GCP) and their ML services (e.g., Azure ML, Vertex AI).
What Will Give You the Competitive Edge (Preferred Qualifications):
* DevSecOps: Proven experience with relevant DevSecOps concepts and tooling, including Continuous Integration/Continuous Delivery (CI/CD), Git SCM, Containerization (Docker, Kubernetes), Infrastructure-as-Code (HashiCorp Terraform).
* Machine Learning Theory: Solid understanding of the theoretical foundations of machine learning algorithms, including deep learning, NLP, and classical ML.
* Problem-Solving: A pragmatic and results-oriented approach to problem-solving, with the ability to translate ambiguous requirements into concrete technical solutions.
* Industry Experience: A broad understanding of life science, covering the business model, regulatory/compliance requirements, risks and rewards.

An ability to identify and execute against opportunities within machine learning that directly support life science outcomes.
* Communication: Excellent communication skills, capable of articulating complex technical decisions and outcomes to both technical and non-technical stakeholders.
Additional Information:
* Location: Global Headquarters- Indianapolis, IN (Hybrid environment)
* Travel: Minimal
Don’t meet every single requirement?

Studies have shown underrecognized groups are less likely to apply to jobs unless they meet every single qualification.

At Elanco we are dedicated to building a diverse and inclusive work environment.

If you think you might be a good fit for a role but don't necessarily meet every requirement, we encourage you to apply.

You may be the right candidate for this role or other roles!
Elanco Benefits and Perks:
We offer a comprehensive benefits package focusing on financial, physical, and mental well-being while encouraging our employees to pursue our purpose! Some highlights include:
* Multiple relocation packages
* Two weeklong shutdowns (mid-summer and year-end) in the US (in addition to PTO)
* 8-week parental leave
* 9 Employee Resource Groups
* Annual bonus offering
* Flexible work arrangements
* Up to 6% 401K matching
Elanco is an EEO/Affirmative Action Employer and does not discriminate on the basis of age, race, color, religion, gender, sexual orientation, gender identity, gender expression, national origin, protected veteran status, disability or any other legally protected status

Required Skill Profession

Computer Occupations


  • Job Details

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Unlock Your Machine Learning Potential: Insight & Career Growth Guide


Real-time Machine Learning Jobs Trends (Graphical Representation)

Explore profound insights with Expertini's real-time, in-depth analysis, showcased through the graph here. Uncover the dynamic job market trends for Machine Learning in Indianapolis, United States, highlighting market share and opportunities for professionals in Machine Learning roles.

11037 Jobs in United States
11037
69 Jobs in Indianapolis
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Are You Looking for Machine Learning Engineer Job?

Great news! is currently hiring and seeking a Machine Learning Engineer to join their team. Feel free to download the job details.

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The Work Culture

An organization's rules and standards set how people should be treated in the office and how different situations should be handled. The work culture at Elanco adheres to the cultural norms as outlined by Expertini.

The fundamental ethical values are:

1. Independence

2. Loyalty

3. Impartiapty

4. Integrity

5. Accountabipty

6. Respect for human rights

7. Obeying United States laws and regulations

What Is the Average Salary Range for Machine Learning Engineer Positions?

The average salary range for a varies, but the pay scale is rated "Standard" in Indianapolis. Salary levels may vary depending on your industry, experience, and skills. It's essential to research and negotiate effectively. We advise reading the full job specification before proceeding with the application to understand the salary package.

What Are the Key Qualifications for Machine Learning Engineer?

Key qualifications for Machine Learning Engineer typically include Computer Occupations and a list of qualifications and expertise as mentioned in the job specification. The generic skills are mostly outlined by the . Be sure to check the specific job listing for detailed requirements and qualifications.

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Interview Tips for Machine Learning Engineer Job Success

Elanco interview tips for Machine Learning Engineer

Here are some tips to help you prepare for and ace your Machine Learning Engineer job interview:

Before the Interview:

Research: Learn about the Elanco's mission, values, products, and the specific job requirements and get further information about

Other Openings

Practice: Prepare answers to common interview questions and rehearse using the STAR method (Situation, Task, Action, Result) to showcase your skills and experiences.

Dress Professionally: Choose attire appropriate for the company culture.

Prepare Questions: Show your interest by having thoughtful questions for the interviewer.

Plan Your Commute: Allow ample time to arrive on time and avoid feeling rushed.

During the Interview:

Be Punctual: Arrive on time to demonstrate professionalism and respect.

Make a Great First Impression: Greet the interviewer with a handshake, smile, and eye contact.

Confidence and Enthusiasm: Project a positive attitude and show your genuine interest in the opportunity.

Answer Thoughtfully: Listen carefully, take a moment to formulate clear and concise responses. Highlight relevant skills and experiences using the STAR method.

Ask Prepared Questions: Demonstrate curiosity and engagement with the role and company.

Follow Up: Send a thank-you email to the interviewer within 24 hours.

Additional Tips:

Be Yourself: Let your personality shine through while maintaining professionalism.

Be Honest: Don't exaggerate your skills or experience.

Be Positive: Focus on your strengths and accomplishments.

Body Language: Maintain good posture, avoid fidgeting, and make eye contact.

Turn Off Phone: Avoid distractions during the interview.

Final Thought:

To prepare for your Machine Learning Engineer interview at Elanco, research the company, understand the job requirements, and practice common interview questions.

Highlight your leadership skills, achievements, and strategic thinking abilities. Be prepared to discuss your experience with HR, including your approach to meeting targets as a team player. Additionally, review the Elanco's products or services and be prepared to discuss how you can contribute to their success.

By following these tips, you can increase your chances of making a positive impression and landing the job!

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