BENGALURU · FULLTIME
AIML Engineer
Onix Networking Corporation
Bengaluru · onsite · Posted 42d ago
Sourced from
Undisclosed6–11 yrsfulltimeBengaluru
About a minute. You'll make an account on the way through.
agent · working
- Read this posting0.7s
- Found the form on Naukri · 9 questions to answer1.1s
- Decided the answers for all of them2.8s
- Tailor your résumé to this role
- Waiting for you
Section · 01
About this role
Job Title: Lead AI/ML Engineer
Job Summary
Roles Responsibilities
1. Model Development Solution Ownership
2. Data Handling Strategy
3. Cloud AI/ML Deployment
4. Team Leadership Mentoring
5. Stakeholder Collaboration
6. Continuous Innovation
Required Skills Qualifications
Preferred Skills
Key Attributes
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Experience Level: 6+ years
Location: [Pune]
Type: Full-Time
Location: [Pune]
Type: Full-Time
Job Summary
We are looking for a highly skilled and motivated Senior/Lead AI/ML Engineer with expertise in Generative AI and hands-on experience in GCP or other cloud platforms. The ideal candidate will have a proven track record of end-to-end project delivery , including design, development, deployment, and monitoring of AI/ML solutions.
In this role, you will take ownership of solution delivery , guide and mentor junior team members, and ensure high-quality, production-ready outcomes. You will leverage advanced frameworks such as MCP, Retrieval-Augmented Generation (RAG), and REACT to build scalable AI/ML systems and play a key role in driving innovation within the organization.
Roles Responsibilities
1. Model Development Solution Ownership
Lead the design, training, and optimization of AI/ML and Generative AI models.
Build and oversee conversational AI solutions, chatbots, and agents using LangChain, RAG, and advanced prompting.
Define architecture choices, trade-offs, and deployment strategies.
Review and validate deliverables from junior engineers.
2. Data Handling Strategy
Oversee large-scale datasets for AI/ML applications, ensuring quality, transformation, and normalization.
Define scalable and reliable data engineering workflows.
Mentor junior team members in data preprocessing, feature engineering, and analysis.
3. Cloud AI/ML Deployment
Lead deployment and optimization of AI/ML workflows on cloud platforms (preferably GCP: Vertex AI, BigQuery, Dataflow).
Ensure production-grade scalability, observability, and retraining pipelines .
Implement cost-efficient and secure deployment strategies.
4. Team Leadership Mentoring
Guide, mentor, and coach junior engineers in coding, debugging, and design reviews.
Build a collaborative team environment that encourages learning and innovation.
Provide technical direction, ensuring adherence to best practices and delivery timelines.
5. Stakeholder Collaboration
Act as a bridge between business stakeholders and the technical team.
Translate business requirements into technical roadmaps.
Communicate risks, trade-offs, and progress clearly to leadership and clients.
6. Continuous Innovation
Stay updated with the latest in Generative AI, LLMs, agent orchestration frameworks, and advanced ML techniques.
Evaluate and adopt new technologies to enhance solutions.
Proactively recommend improvements in architecture, processes, and delivery.
Required Skills Qualifications
6+ years of experience in AI/ML solution development and deployment.
Proven track record of end-to-end ownership of AI/ML projects .
Strong programming skills in Python and SQL.
Hands-on experience with Generative AI, LLMs, RAG, LangChain, MCP, and orchestration frameworks .
Deep understanding of ML algorithms, statistical methods, and embeddings.
Experience with cloud-native AI/ML workflows (Vertex AI, BigQuery, Dataflow, Cloud Functions).
Strong grasp of MLOps pipelines : CI/CD, monitoring, and retraining workflows.
Demonstrated experience mentoring and guiding junior engineers.
Knowledge of Docker/Kubernetes for deployment and containerization.
Preferred Skills
Familiarity with Reinforcement Learning from Human Feedback (RLHF) .
Exposure to AI governance, compliance, and security best practices .
Experience leading small-to-medium teams in delivery-focused environments.
Knowledge of cost optimization strategies in cloud AI solutions.
Hands-on with advanced agent frameworks (e.g., REACT, Agent-to-Agent orchestration).
Key Attributes
Strong analytical, debugging, and problem-solving skills.
Leadership, accountability, and ownership mindset.
Ability to mentor and uplift junior engineers while meeting deadlines.
Excellent communication skills with both technical and non-technical stakeholders.
Proactive learner with the ability to adapt quickly to new technologies.
Disclaimer: This job posting has been aggregated from external source. Role details, content, and availability are subject to change. Applicants are advised to confirm the latest information directly on the company website before applying.
Sourced from naukri
Section · 02
Skills
Dockercloud platformscloud aidata handlingBusiness Requirementsbigqueryai governanceConversational AiGoogle Cloud FunctionsData EngineeringcloudCommunication SkillsAlgorithmsArchitecturecomplianceArtificial Intelligence